diff --git a/docs/conceptual/command-processor.rst b/docs/conceptual/command-processor.rst index a055768a1..567f7ceec 100644 --- a/docs/conceptual/command-processor.rst +++ b/docs/conceptual/command-processor.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Command processor (CP) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, command, processor, fetcher, packet processor, CPF, CPC + :description: ROCm Compute Profiler performance model: Command processor (CP) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, command, processor, fetcher, packet processor, CPF, CPC ********************** Command processor (CP) diff --git a/docs/conceptual/compute-unit.rst b/docs/conceptual/compute-unit.rst index e7061c814..3b265d26b 100644 --- a/docs/conceptual/compute-unit.rst +++ b/docs/conceptual/compute-unit.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Compute unit (CU) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, GCN, compute, unit, pipeline, workgroup, wavefront, + :description: ROCm Compute Profiler performance model: Compute unit (CU) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, GCN, compute, unit, pipeline, workgroup, wavefront, CDNA ***************** @@ -19,7 +19,7 @@ CDNA™-based accelerators. All :ref:`wavefronts ` of a The CU consists of several independent execution pipelines and functional units. The :doc:`/conceptual/pipeline-descriptions` section details the various execution pipelines -- VALU, SALU, LDS, scheduler, and so forth. The metrics -presented by Omniperf for these pipelines are described in +presented by ROCm Compute Profiler for these pipelines are described in :doc:`pipeline-metrics`. The :doc:`vL1D ` cache and :doc:`LDS ` are described in their own sections. diff --git a/docs/conceptual/definitions.rst b/docs/conceptual/definitions.rst index 8ad483094..f0d1e9e0e 100644 --- a/docs/conceptual/definitions.rst +++ b/docs/conceptual/definitions.rst @@ -1,13 +1,13 @@ .. meta:: - :description: Omniperf terminology and definitions - :keywords: Omniperf, ROCm, glossary, definitions, terms, profiler, tool, + :description: ROCm Compute Profiler terminology and definitions + :keywords: Omniperf, ROCm Compute Profiler, ROCm, glossary, definitions, terms, profiler, tool, Instinct, accelerator, AMD *********** Definitions *********** -The following table briefly defines some terminology used in Omniperf interfaces +The following table briefly defines some terminology used in ROCm Compute Profiler interfaces and in this documentation. .. include:: ./includes/terms.rst diff --git a/docs/conceptual/includes/normalization-units.rst b/docs/conceptual/includes/normalization-units.rst index 34961f7e0..365c30c0e 100644 --- a/docs/conceptual/includes/normalization-units.rst +++ b/docs/conceptual/includes/normalization-units.rst @@ -34,7 +34,7 @@ include: that is, the total runtime of the kernel in seconds, as measured by the :doc:`command processor `. -By default, Omniperf uses the ``per_wave`` normalization. +By default, ROCm Compute Profiler uses the ``per_wave`` normalization. .. tip:: diff --git a/docs/conceptual/l2-cache.rst b/docs/conceptual/l2-cache.rst index 2c4b44514..6d0f26c09 100644 --- a/docs/conceptual/l2-cache.rst +++ b/docs/conceptual/l2-cache.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: L2 cache (TCC) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, L2, cache, infinity fabric, metrics + :description: ROCm Compute Profiler performance model: L2 cache (TCC) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, L2, cache, infinity fabric, metrics ************** L2 cache (TCC) @@ -21,7 +21,7 @@ across the L2 channels. Requests that miss in the L2 cache are passed out to :ref:`Infinity Fabric™ ` to be routed to the appropriate memory location. -The L2 cache metrics reported by Omniperf are broken down into four +The L2 cache metrics reported by ROCm Compute Profiler are broken down into four categories: * :ref:`L2 Speed-of-Light ` @@ -299,7 +299,7 @@ accelerator’s memory, or even in the CPU’s memory. Infinity Fabric is responsible for routing these memory requests/data to the correct location and returning any fetched data to the L2 cache. The :ref:`l2-request-flow` describes the flow of these requests through -Infinity Fabric in more detail, as described by Omniperf metrics, +Infinity Fabric in more detail, as described by ROCm Compute Profiler metrics, while :ref:`l2-request-metrics` give detailed definitions of individual metrics. @@ -309,7 +309,7 @@ Request flow ------------ The following is a diagram that illustrates how L2↔Fabric requests are reported -by Omniperf: +by ROCm Compute Profiler: .. figure:: ../data/performance-model/fabric.png :align: center diff --git a/docs/conceptual/local-data-share.rst b/docs/conceptual/local-data-share.rst index c596844dc..8035def62 100644 --- a/docs/conceptual/local-data-share.rst +++ b/docs/conceptual/local-data-share.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Local data share (LDS) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, local, data, share, LDS + :description: ROCm Compute Profiler performance model: Local data share (LDS) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, local, data, share, LDS ********************** Local data share (LDS) diff --git a/docs/conceptual/performance-model.rst b/docs/conceptual/performance-model.rst index 1a94b3ed6..191a3ca3f 100644 --- a/docs/conceptual/performance-model.rst +++ b/docs/conceptual/performance-model.rst @@ -1,13 +1,13 @@ .. meta:: - :description: Omniperf performance model - :keywords: Omniperf, ROCm, performance, model, profiler, tool, Instinct, + :description: ROCm Compute Profiler performance model + :keywords: Omniperf, ROCm Compute Profiler, ROCm, performance, model, profiler, tool, Instinct, accelerator, AMD ***************** Performance model ***************** -Omniperf makes available an extensive list of metrics to better understand +ROCm Compute Profiler makes available an extensive list of metrics to better understand achieved application performance on AMD Instinct™ MI-series accelerators including Graphics Core Next™ (GCN) GPUs like the AMD Instinct MI50, CDNA™ accelerators like the MI100, and CDNA2 accelerators such as the MI250X, MI250, @@ -18,7 +18,7 @@ hardware blocks of AMD Instinct accelerators. This section describes each hardware block on the accelerator as interacted with by a software developer to give a deeper understanding of the metrics reported by profiling data. Refer to :doc:`/tutorial/profiling-by-example` for more practical examples and details on how -to use Omniperf to optimize your code. +to use ROCm Compute Profiler to optimize your code. .. _mixxx-note: @@ -34,7 +34,7 @@ to use Omniperf to optimize your code. :prod-page:`MI250 `, and :prod-page:`MI210 ` product pages. -In this chapter, the AMD Instinct performance model used by Omniperf is divided into a handful of +In this chapter, the AMD Instinct performance model used by ROCm Compute Profiler is divided into a handful of key hardware blocks, each detailed in the following sections: * :doc:`compute-unit` diff --git a/docs/conceptual/pipeline-descriptions.rst b/docs/conceptual/pipeline-descriptions.rst index 9261421eb..c842747aa 100644 --- a/docs/conceptual/pipeline-descriptions.rst +++ b/docs/conceptual/pipeline-descriptions.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Shader engine (SE) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, pipeline, VALU, SALU, VMEM, SMEM, LDS, branch, + :description: ROCm Compute Profiler performance model: Shader engine (SE) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, pipeline, VALU, SALU, VMEM, SMEM, LDS, branch, scheduler, MFMA, AGPRs ********************* @@ -101,7 +101,7 @@ coordinate between wavefronts in a workgroup. Performance model of the local data share (LDS) on AMD Instinct MI-series accelerators. -Above is Omniperf's performance model of the LDS on CDNA accelerators (adapted +Above is ROCm Compute Profiler's performance model of the LDS on CDNA accelerators (adapted from :mantor-gcn-pdf:`20`). The SIMDs in the :ref:`VALU ` are connected to the LDS in pairs (see above). Only one SIMD per pair may issue an LDS instruction at a time, but both pairs may issue concurrently. @@ -186,7 +186,7 @@ shadow (see the :ref:`MFMA ` section for more detail). .. note:: - The IPC model used by Omniperf omits the following two complications for + The IPC model used by ROCm Compute Profiler omits the following two complications for clarity. First, CDNA accelerators contain other execution units on the CU that are unused for compute applications. Second, so-called "internal" instructions (see :gcn-crash-course:`29`) are not issued to a functional @@ -237,7 +237,7 @@ various AMD accelerators (including the CDNA line), we recommend the GPRs required for D: 4 GPR alignment requirement: 8 bytes -For the purposes of Omniperf, the MFMA unit is typically treated as a separate +For the purposes of ROCm Compute Profiler, the MFMA unit is typically treated as a separate pipeline from the :ref:`VALU `, as other VALU instructions (along with other execution pipelines such as the :ref:`SALU `) typically can be issued during a portion of the total duration of an MFMA operation. diff --git a/docs/conceptual/pipeline-metrics.rst b/docs/conceptual/pipeline-metrics.rst index f7bb4bcda..5caaa3733 100644 --- a/docs/conceptual/pipeline-metrics.rst +++ b/docs/conceptual/pipeline-metrics.rst @@ -1,13 +1,13 @@ .. meta:: - :description: Omniperf performance model: Pipeline metrics - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, pipeline, wavefront, metrics, launch, runtime + :description: ROCm Compute Profiler performance model: Pipeline metrics + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, pipeline, wavefront, metrics, launch, runtime VALU, MFMA, instruction mix, FLOPs, arithmetic, operations **************** Pipeline metrics **************** -In this section, we describe the metrics available in Omniperf to analyze the +In this section, we describe the metrics available in ROCm Compute Profiler to analyze the pipelines discussed in the :doc:`pipeline-descriptions`. .. _wavefront: @@ -233,7 +233,7 @@ Instruction mix The instruction mix panel shows a breakdown of the various types of instructions executed by the user’s kernel, and which pipelines on the -:doc:`CU ` they were executed on. In addition, Omniperf reports +:doc:`CU ` they were executed on. In addition, ROCm Compute Profiler reports further information about the breakdown of operation types for the :ref:`VALU `, vector-memory, and :ref:`MFMA ` instructions. @@ -555,7 +555,7 @@ Compute pipeline FLOP counting conventions ------------------------- -Omniperf’s conventions for VALU FLOP counting are as follows: +ROCm Compute Profiler’s conventions for VALU FLOP counting are as follows: * Addition or multiplication: 1 operation diff --git a/docs/conceptual/references.rst b/docs/conceptual/references.rst index 9f3d32cd8..4ed88dd86 100644 --- a/docs/conceptual/references.rst +++ b/docs/conceptual/references.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: References - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, HIP, GCN, LLVM, docs, documentation, training + :description: ROCm Compute Profiler performance model: References + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, HIP, GCN, LLVM, docs, documentation, training ********** References diff --git a/docs/conceptual/shader-engine.rst b/docs/conceptual/shader-engine.rst index 8295c4516..75952ad00 100644 --- a/docs/conceptual/shader-engine.rst +++ b/docs/conceptual/shader-engine.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Shader engine (SE) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, shader, engine, sL1D, L1I, workgroup manager, SPI + :description: ROCm Compute Profiler performance model: Shader engine (SE) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, shader, engine, sL1D, L1I, workgroup manager, SPI ****************** Shader engine (SE) @@ -21,7 +21,7 @@ The number of CUs on a SE varies from chip to chip -- see for example :hip-training-pdf:`20`. In addition, newer accelerators such as the AMD Instinct™ MI 250X have 8 SEs per accelerator. -For the purposes of Omniperf, we consider resources that are shared between +For the purposes of ROCm Compute Profiler, we consider resources that are shared between multiple CUs on a single SE as part of the SE's metrics. These include: @@ -487,7 +487,7 @@ issuing concurrently). .. note:: - Current versions of the profiling libraries underlying Omniperf attempt to + Current versions of the profiling libraries underlying ROCm Compute Profiler attempt to serialize concurrent kernels running on the accelerator, as the performance counters on the device are global (that is, shared between concurrent kernels). This means that these scheduler-pipe utilization metrics are diff --git a/docs/conceptual/system-speed-of-light.rst b/docs/conceptual/system-speed-of-light.rst index f01be4b67..3de2120b3 100644 --- a/docs/conceptual/system-speed-of-light.rst +++ b/docs/conceptual/system-speed-of-light.rst @@ -1,13 +1,13 @@ .. meta:: - :description: Omniperf performance model: System Speed-of-Light - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, system, speed of light + :description: ROCm Compute Profiler performance model: System Speed-of-Light + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, system, speed of light ********************* System Speed-of-Light ********************* System Speed-of-Light summarizes some of the key metrics from various sections -of Omniperf’s profiling report. +of ROCm Compute Profiler’s profiling report. .. warning:: diff --git a/docs/conceptual/vector-l1-cache.rst b/docs/conceptual/vector-l1-cache.rst index 086c195be..3eb5f9f89 100644 --- a/docs/conceptual/vector-l1-cache.rst +++ b/docs/conceptual/vector-l1-cache.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf performance model: Vector L1 cache (vL1D) - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, vector, l1, cache, vl1d + :description: ROCm Compute Profiler performance model: Vector L1 cache (vL1D) + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, vector, l1, cache, vl1d ********************** Vector L1 cache (vL1D) @@ -124,7 +124,7 @@ passes information about the commands (coalescing state, destination SIMD, etc.) to the :ref:`data processing unit ` for use after the requested data has been retrieved. -Omniperf reports several metrics to indicate performance bottlenecks in +ROCm Compute Profiler reports several metrics to indicate performance bottlenecks in the address processing unit, which are broken down into a few categories: @@ -378,7 +378,7 @@ Translation Cache (UTCL1). This cache contains a L1 Translation Lookaside Buffer (TLB) which stores recently translated addresses to reduce the cost of subsequent re-translations. -Omniperf reports the following L1 TLB metrics: +ROCm Compute Profiler reports the following L1 TLB metrics: .. list-table:: :header-rows: 1 @@ -656,7 +656,7 @@ latencies of read/write memory operations to the :doc:`L2 cache `. :ref:`Cache access metrics ` section when evaluating the vL1D hit rate. -.. [#vl1d-activity] Omniperf considers the vL1D to be active when any part of +.. [#vl1d-activity] ROCm Compute Profiler considers the vL1D to be active when any part of the vL1D (excluding the :ref:`address processor ` and :ref:`data return ` units) are active, for example, when performing a translation, waiting for data, accessing the Tag or Cache RAMs, etc. @@ -685,7 +685,7 @@ from the :ref:`VALU `. When data is returned from the :ref:`vL1D cache RAM `, it is matched to this previously stored request data, and returned to the appropriate SIMD. -Omniperf reports the following vL1D data-return path metrics: +ROCm Compute Profiler reports the following vL1D data-return path metrics: .. list-table:: :header-rows: 1 diff --git a/docs/conf.py b/docs/conf.py index f74f95ecd..95c0012cd 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -35,7 +35,7 @@ version_number = match[1] # project info -project = "Omniperf" +project = "ROCm Compute Profiler" author = "Advanced Micro Devices, Inc." copyright = "Copyright (c) 2024 Advanced Micro Devices, Inc. All rights reserved." version = version_number @@ -51,11 +51,14 @@ html_css_files = ["o_custom.css"] external_toc_path = "./sphinx/_toc.yml" -external_projects_current_project = "omniperf" +external_projects_current_project = "rocprofiler-compute" # frequently used external resources extlinks = { - "dev-sample": ("https://github.com/ROCm/omniperf/blob/amd-mainline/sample/%s", "%s"), + "dev-sample": ( + "https://github.com/ROCm/rocprofiler-compute/blob/amd-mainline/sample/%s", + "%s", + ), "prod-page": ( "https://www.amd.com/en/products/accelerators/instinct/%s.html", "%s", diff --git a/docs/data/install/install-decision-tree.png b/docs/data/install/install-decision-tree.png index 1c62fba87..6fe99b01b 100644 Binary files a/docs/data/install/install-decision-tree.png and b/docs/data/install/install-decision-tree.png differ diff --git a/docs/data/unused/install-decision-tree.png b/docs/data/unused/install-decision-tree.png new file mode 100644 index 000000000..1c62fba87 Binary files /dev/null and b/docs/data/unused/install-decision-tree.png differ diff --git a/docs/how-to/analyze/cli.rst b/docs/how-to/analyze/cli.rst index 44a014a8b..f73333f37 100644 --- a/docs/how-to/analyze/cli.rst +++ b/docs/how-to/analyze/cli.rst @@ -1,14 +1,14 @@ .. meta:: - :description: Omniperf analysis: CLI analysis - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, command line, analyze, filtering, metrics, baseline, comparison + :description: ROCm Compute Profiler analysis: CLI analysis + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, command line, analyze, filtering, metrics, baseline, comparison ************ CLI analysis ************ -This section provides an overview of Omniperf's CLI analysis features. +This section provides an overview of ROCm Compute Profiler's CLI analysis features. -* :ref:`Derived metrics `: All of Omniperf's built-in metrics. +* :ref:`Derived metrics `: All of ROCm Compute Profiler's built-in metrics. * :ref:`Baseline comparison `: Compare multiple runs in a side-by-side manner. @@ -19,28 +19,28 @@ This section provides an overview of Omniperf's CLI analysis features. * :ref:`Filtering `: Hone in on a particular kernel, GPU ID, or dispatch ID via post-process filtering. -Run ``omniperf analyze -h`` for more details. +Run ``rocprof-compute analyze -h`` for more details. .. _cli-walkthrough: Walkthrough =========== -1. To begin, generate a high-level analysis report using Omniperf's ``-b`` (or ``--block``) flag. +1. To begin, generate a high-level analysis report using ROCm Compute Profiler's ``-b`` (or ``--block``) flag. - .. code-block:: shell + .. code-block:: shell-session - $ omniperf analyze -p workloads/vcopy/MI200/ -b 2 + $ rocprof-compute analyze -p workloads/vcopy/MI200/ -b 2 - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| Analysis mode = cli - [analysis] deriving Omniperf metrics... + [analysis] deriving rocprofiler-compute metrics... -------------------------------------------------------------------------------- 0. Top Stats @@ -134,19 +134,19 @@ Walkthrough 2. Use ``--list-metrics`` to generate a list of available metrics for inspection. - .. code-block:: shell + .. code-block:: shell-session - $ omniperf analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a + $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| Analysis mode = cli - [analysis] deriving Omniperf metrics... + [analysis] deriving rocprofiler-compute metrics... 0 -> Top Stats 1 -> System Info 2 -> System Speed-of-Light @@ -186,13 +186,13 @@ Walkthrough 3. Choose your own customized subset of metrics with the ``-b`` (or ``--block``) option. Or, build your own configuration following - `config_template `_. + `config_template `_. The following snippet shows how to generate a report containing only metric 2 (:doc:`System Speed-of-Light `). - .. code-block:: shell + .. code-block:: shell-session - $ omniperf analyze -p workloads/vcopy/MI200/ -b 2 + $ rocprof-compute analyze -p workloads/vcopy/MI200/ -b 2 -------- Analyze @@ -280,7 +280,7 @@ Walkthrough 4. Optimize the application, iterate, and re-profile to inspect performance changes. -5. Redo a comprehensive analysis with Omniperf CLI at any optimization +5. Redo a comprehensive analysis with ROCm Compute Profiler CLI at any optimization milestone. .. _cli-analysis-options: @@ -291,22 +291,22 @@ More analysis options Single run .. code-block:: shell - $ omniperf analyze -p workloads/vcopy/MI200/ + $ rocprof-compute analyze -p workloads/vcopy/MI200/ List top kernels and dispatches .. code-block:: shell - $ omniperf analyze -p workloads/vcopy/MI200/ --list-stats + $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-stats List metrics .. code-block:: shell - $ omniperf analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a + $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-metrics gfx90a Show System Speed-of-Light and CS_Busy blocks only .. code-block:: shell - $ omniperf analyze -p workloads/vcopy/MI200/ -b 2 5.1.0 + $ rocprof-compute analyze -p workloads/vcopy/MI200/ -b 2 5.1.0 .. note:: @@ -319,10 +319,10 @@ Filter kernels .. code-block:: - $ omniperf analyze -p workloads/vcopy/MI200/ --list-stats + $ rocprof-compute analyze -p workloads/vcopy/MI200/ --list-stats Analysis mode = cli - [analysis] deriving Omniperf metrics... + [analysis] deriving rocprofiler-compute metrics... -------------------------------------------------------------------------------- Detected Kernels (sorted descending by duration) @@ -344,12 +344,12 @@ Filter kernels ``vecCopy(double*, double*, double*, int, int) [clone .kd]`` at index ``0``. Then, use this index to apply the filter via ``-k`` or ``--kernels``. - .. code-block:: shell + .. code-block:: shell-session - $ omniperf analyze -p workloads/vcopy/MI200/ -k 0 + $ rocprof-compute analyze -p workloads/vcopy/MI200/ -k 0 Analysis mode = cli - [analysis] deriving Omniperf metrics... + [analysis] deriving rocprofiler-compute metrics... -------------------------------------------------------------------------------- 0. Top Stats @@ -369,10 +369,10 @@ Filter kernels Baseline comparison .. code-block:: shell - omniperf analyze -p workload1/path/ -p workload2/path/ + rocprof-compute analyze -p workload1/path/ -p workload2/path/ OR .. code-block:: shell - omniperf analyze -p workload1/path/ -k 0 -p workload2/path/ -k 1 + rocprof-compute analyze -p workload1/path/ -k 0 -p workload2/path/ -k 1 diff --git a/docs/how-to/analyze/grafana-gui.rst b/docs/how-to/analyze/grafana-gui.rst index d5474aefb..110347911 100644 --- a/docs/how-to/analyze/grafana-gui.rst +++ b/docs/how-to/analyze/grafana-gui.rst @@ -1,6 +1,7 @@ .. meta:: - :description: Omniperf analysis: Grafana GUI - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, Grafana, panels, GUI, import + :description: ROCm Compute Profiler analysis: Grafana GUI + :keywords: Omniperf, ROCm Compute Profiler, ROCm, profiler, tool, + Instinct, accelerator, Grafana, panels, GUI, import ******************** Grafana GUI analysis @@ -8,7 +9,7 @@ Grafana GUI analysis Find setup instructions in :doc:`../../install/grafana-setup`. -The Omniperf Grafana analysis dashboard GUI supports the following features to +The ROCm Compute Profiler Grafana analysis dashboard GUI supports the following features to facilitate MI accelerator performance profiling and analysis: * System and hardware component (hardware block) @@ -40,7 +41,7 @@ facilitate MI accelerator performance profiling and analysis: * L2 Cache (TCC) (both aggregated and per-channel perf info) -See the full list of :ref:`Omniperf's analysis panels `. +See the full list of :ref:`ROCm Compute Profiler's analysis panels `. .. _analysis-sol: @@ -70,14 +71,14 @@ normalizations are available. * ``per_second`` -See :ref:`normalization-units` to learn more about Omniperf normalizations. +See :ref:`normalization-units` to learn more about ROCm Compute Profiler normalizations. .. _analysis-baseline-comparison: Baseline comparison ------------------- -Omniperf enables baseline comparison to allow checking A/B effect. Currently +ROCm Compute Profiler enables baseline comparison to allow checking A/B effect. Currently baseline comparison is limited to the same :ref:`SoC `. Cross comparison between SoCs is in development. @@ -92,14 +93,14 @@ setup the following filters to allow fine grained comparisons: * Dispatch ID filtering (regex filtering) -* Omniperf Panels (multi-selection) +* ROCm Compute Profiler Panels (multi-selection) .. _analysis-regex-dispatch-id: Regex-based dispatch ID filtering --------------------------------- -Omniperf allows filtering via Regular Expressions (regex), a standard Linux +ROCm Compute Profiler allows filtering via Regular Expressions (regex), a standard Linux string matching syntax, based dispatch ID filtering to flexibly choose the kernel invocations. @@ -116,7 +117,7 @@ corresponding regex is : ``(1[7-9]|[23]\d|4[0-8])``. Incremental profiling --------------------- -Omniperf supports incremental profiling to speed up performance analysis. +ROCm Compute Profiler supports incremental profiling to speed up performance analysis. Refer to the :ref:`profiling-hw-component-filtering` section for this command. @@ -145,7 +146,7 @@ Global variables and configurations .. image:: ../../data/analyze/global_variables.png :align: center - :alt: Omniperf global variables and configurations + :alt: ROCm Compute Profiler global variables and configurations :width: 800 .. _grafana-gui-import: @@ -153,7 +154,7 @@ Global variables and configurations Grafana GUI import ------------------ -The Omniperf database ``--import`` option imports the raw profiling data to +The ROCm Compute Profiler database ``--import`` option imports the raw profiling data to Grafana's backend MongoDB database. This step is only required for Grafana GUI-based performance analysis. @@ -169,13 +170,13 @@ convention: .. code-block:: shell - omniperf___ + rocprofiler-compute___ For example: .. code-block:: shell - omniperf_asw_vcopy_mi200 + rocprofiler-compute_asw_vcopy_mi200 When using :ref:`database mode `, be sure to tailor the connection options to the machine hosting your @@ -187,10 +188,10 @@ called ``dummybox``. .. code-block:: shell-session - $ omniperf database --help + $ rocprof-compute database --help usage: - omniperf database [connection options] + rocprof-compute database [connection options] @@ -198,9 +199,9 @@ called ``dummybox``. Examples: - omniperf database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/ + rocprof-compute database --import -H pavii1 -u temp -t asw -w workloads/vcopy/mi200/ - omniperf database --remove -H pavii1 -u temp -w omniperf_asw_sample_mi200 + rocprof-compute database --remove -H pavii1 -u temp -w rocprofiler-compute_asw_sample_mi200 ------------------------------------------------------------------------------- @@ -215,8 +216,8 @@ called ``dummybox``. -s, --specs Print system specs. Interaction Type: - -i, --import Import workload to Omniperf DB - -r, --remove Remove a workload from Omniperf DB + -i, --import Import workload to ROCm Compute Profiler DB + -r, --remove Remove a workload from ROCm Compute Profiler DB Connection Options: -H , --host Name or IP address of the server host. @@ -228,22 +229,22 @@ called ``dummybox``. --kernel-verbose Specify Kernel Name verbose level 1-5. Lower the level, shorter the kernel name. (DEFAULT: 5) (DISABLE: 5) -Omniperf import for vcopy: -^^^^^^^^^^^^^^^^^^^^^^^^^^ +ROCm Compute Profiler import for vcopy: +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -.. code-block:: shell +.. code-block:: shell-session - $ omniperf database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/ + $ rocprof-compute database --import -H dummybox -u temp -t asw -w workloads/vcopy/mi200/ - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| - Pulling data from /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Pulling data from /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 The directory exists Found sysinfo file KernelName shortening enabled @@ -251,15 +252,15 @@ Omniperf import for vcopy: Password: Password received -- Conversion & Upload in Progress -- - 0%| | 0/11 [00:00 @@ -871,7 +872,7 @@ Texture Addresser .. figure:: ../../data/analyze/grafana/ta_panel.png :align: center - :alt: Texture Addresser in Omniperf Grafana + :alt: Texture Addresser in ROCm Compute Profiler Grafana :width: 800 Metric specific to texture addresser (TA) which receives commands (e.g., @@ -889,7 +890,7 @@ Texture Data .. figure:: ../../data/analyze/grafana/td_panel.png :align: center - :alt: Texture Data panel in Omniperf Grafana + :alt: Texture Data panel in ROCm Compute Profiler Grafana :width: 800 Metrics specific to texture data (TD) which routes data back to the @@ -909,7 +910,7 @@ Speed-of-Light .. figure:: ../../data/analyze/grafana/vl1d-sol_panel.png :align: center - :alt: Speed-of-Light (VL1D) panel in Omniperf Grafana + :alt: Speed-of-Light (VL1D) panel in ROCm Compute Profiler Grafana :width: 800 Key metrics of the vector L1 data (vL1D) cache as a comparison with the peak @@ -924,7 +925,7 @@ L1D Cache Stalls .. figure:: ../../data/analyze/grafana/vl1d-cache-stalls_panel.png :align: center - :alt: L1D Cache Stalls panel in Omniperf Grafana + :alt: L1D Cache Stalls panel in ROCm Compute Profiler Grafana :width: 800 More detail on where vector L1 data (vL1D) cache is stalled in the pipeline, @@ -955,7 +956,7 @@ L1D - L2 Transactions .. figure:: ../../data/analyze/grafana/vl1d-l2-transactions_panel.png :align: center - :alt: L1D - L2 Transactions in Omniperf Grafana + :alt: L1D - L2 Transactions in ROCm Compute Profiler Grafana :width: 800 A more granular look at the types of requests made to the L2 cache. @@ -969,7 +970,7 @@ L1D Addr Translation .. figure:: ../../data/analyze/grafana/vl1d-addr-translation_panel.png :align: center - :alt: L1D Addr Translation panel in Omniperf Grafana + :alt: L1D Addr Translation panel in ROCm Compute Profiler Grafana :width: 800 After a vector memory instruction has been processed/coalesced by the address @@ -995,7 +996,7 @@ Speed-of-Light .. figure:: ../../data/analyze/grafana/l2-sol_panel.png :align: center - :alt: Speed-of-Light (L2 cache) panel in Omniperf Grafana + :alt: Speed-of-Light (L2 cache) panel in ROCm Compute Profiler Grafana :width: 800 Key metrics about the performance of the L2 cache, aggregated over all the @@ -1011,7 +1012,7 @@ L2 Cache Accesses .. figure:: ../../data/analyze/grafana/l2-accesses_panel.png :align: center - :alt: L2 Cache Accesses panel in Omniperf Grafana + :alt: L2 Cache Accesses panel in ROCm Compute Profiler Grafana :width: 800 Incoming requests to the L2 cache from the vector L1 data (vL1D) cache and @@ -1026,7 +1027,7 @@ L2 - Fabric Transactions .. figure:: ../../data/analyze/grafana/l2-fabric-transactions_panel.png :align: center - :alt: L2 - Fabric Transactions panel in Omniperf Grafana + :alt: L2 - Fabric Transactions panel in ROCm Compute Profiler Grafana :width: 800 More detail on the flow of requests through Infinity Fabric™. @@ -1040,7 +1041,7 @@ L2 - Fabric Interface Stalls .. figure:: ../../data/analyze/grafana/l2-fabric-interface-stalls_panel.png :align: center - :alt: L2 - Fabric Interface Stalls panel in Omniperf Grafana + :alt: L2 - Fabric Interface Stalls panel in ROCm Compute Profiler Grafana :width: 800 A breakdown of what types of requests in a kernel caused a stall @@ -1065,7 +1066,7 @@ Aggregate Stats .. figure:: ../../data/analyze/grafana/l2-per-channel-agg-stats_panel.png :align: center - :alt: Aggregate Stats (L2 cache per channel) panel in Omniperf Grafana + :alt: Aggregate Stats (L2 cache per channel) panel in ROCm Compute Profiler Grafana :width: 800 L2 Cache per channel performance at a glance. Metrics are aggregated over all available channels. diff --git a/docs/how-to/analyze/mode.rst b/docs/how-to/analyze/mode.rst index b34e1214c..d9f802cdb 100644 --- a/docs/how-to/analyze/mode.rst +++ b/docs/how-to/analyze/mode.rst @@ -1,22 +1,22 @@ .. meta:: - :description: How to use Omniperf's analyze mode - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: How to use ROCm Compute Profiler's analyze mode + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, Grafana, analysis, analyze mode ************ Analyze mode ************ -Omniperf offers several ways to interact with the metrics it generates from +ROCm Compute Profiler offers several ways to interact with the metrics it generates from profiling. Your level of familiarity with the profiled application, computing -environment, and experience with Omniperf should inform the analysis method you +environment, and experience with ROCm Compute Profiler should inform the analysis method you choose. -While analyzing with the CLI offers quick and straightforward access to Omniperf +While analyzing with the CLI offers quick and straightforward access to ROCm Compute Profiler metrics from the terminal, Grafana's dashboard GUI adds an extra layer of readability and interactivity you might prefer. -See the following sections to explore Omniperf's analysis and visualization +See the following sections to explore ROCm Compute Profiler's analysis and visualization options. * :doc:`cli` @@ -32,5 +32,5 @@ options. Unless otherwise noted, the performance analysis is done on the :ref:`MI200 platform `. -Learn about profiling with Omniperf in :doc:`../profile/mode`. For an overview of -Omniperf's other modes, see :ref:`modes`. +Learn about profiling with ROCm Compute Profiler in :doc:`../profile/mode`. For an overview of +ROCm Compute Profiler's other modes, see :ref:`modes`. diff --git a/docs/how-to/analyze/standalone-gui.rst b/docs/how-to/analyze/standalone-gui.rst index 15bd00878..f138c1124 100644 --- a/docs/how-to/analyze/standalone-gui.rst +++ b/docs/how-to/analyze/standalone-gui.rst @@ -1,15 +1,15 @@ .. meta:: - :description: Omniperf analysis: Standalone GUI + :description: ROCm Compute Profiler analysis: Standalone GUI :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, GUI, standalone, filter *********************** Standalone GUI analysis *********************** -Omniperf's standalone analysis GUI is a lightweight web page that you can +ROCm Compute Profiler's standalone analysis GUI is a lightweight web page that you can generate straight from the command line. The standalone analysis GUI is an alternative to the CLI if you want to explore profiling results visually, but -without the additional setup requirements or server-side overhead of Omniperf's +without the additional setup requirements or server-side overhead of ROCm Compute Profiler's detailed :doc:`Grafana interface ` option. This analysis option is implemented as a simple `Flask `_ application that lets you view results from your preferred web browser. @@ -29,22 +29,22 @@ application that lets you view results from your preferred web browser. Launch the standalone GUI analyzer ---------------------------------- -To launch the Omniperf GUI analyzer, include the ``--gui`` flag with your +To launch the ROCm Compute Profiler GUI analyzer, include the ``--gui`` flag with your desired analysis command. For example: -.. code-block:: shell +.. code-block:: shell-session - $ omniperf analyze -p workloads/vcopy/MI200/ --gui + $ rocprof-compute analyze -p workloads/vcopy/MI200/ --gui - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| Analysis mode = web_ui - [analysis] deriving Omniperf metrics... + [analysis] deriving rocprofiler-compute metrics... Dash is running on http://0.0.0.0:8050/ * Serving Flask app 'rocprof_compute_analyze.analysis_webui' (lazy loading) @@ -62,7 +62,7 @@ At this point, you can launch your web browser of choice and navigate to .. image:: ../../data/analyze/standalone_gui.png :align: center - :alt: Omniperf standalone GUI home screen + :alt: ROCm Compute Profiler standalone GUI home screen :width: 800 .. tip:: @@ -85,5 +85,5 @@ metrics specific to your selected filters. Once a filter is applied, you'll see several additional sections become available with detailed metrics specific to that area of AMD hardware. These -detailed sections mirror the data displayed in Omniperf's +detailed sections mirror the data displayed in ROCm Compute Profiler's :doc:`Grafana interface `. diff --git a/docs/how-to/profile/mode.rst b/docs/how-to/profile/mode.rst index 5bc0ad6a7..1a5472399 100644 --- a/docs/how-to/profile/mode.rst +++ b/docs/how-to/profile/mode.rst @@ -1,27 +1,27 @@ .. meta:: - :description: How to use Omniperf's profile mode - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: How to use ROCm Compute Profiler's profile mode + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, profiling, profile mode ************ Profile mode ************ -The following chapter walks you through Omniperf's core profiling features by +The following chapter walks you through ROCm Compute Profiler's core profiling features by example. -Learn about analysis with Omniperf in :doc:`../analyze/mode`. For an overview of -Omniperf's other modes, see :ref:`modes`. +Learn about analysis with ROCm Compute Profiler in :doc:`../analyze/mode`. For an overview of +ROCm Compute Profiler's other modes, see :ref:`modes`. Profiling ========= -Use the ``omniperf`` executable to acquire all necessary performance monitoring +Use the ``rocprof-compute`` executable to acquire all necessary performance monitoring data through analysis of compute workloads. -Profiling with Omniperf yields the following benefits. +Profiling with ROCm Compute Profiler yields the following benefits. -* :ref:`Automate counter collection `: Omniperf handles all +* :ref:`Automate counter collection `: ROCm Compute Profiler handles all of your profiling via pre-configured input files. * :ref:`Filtering `: Apply runtime filters to speed up the profiling @@ -30,7 +30,7 @@ Profiling with Omniperf yields the following benefits. * :ref:`Standalone roofline `: Isolate a subset of built-in metrics or build your own profiling configuration. -Run ``omniperf profile -h`` for more details. See +Run ``rocprof-compute profile -h`` for more details. See :ref:`Basic usage `. .. _profile-example: @@ -38,14 +38,14 @@ Run ``omniperf profile -h`` for more details. See Profiling example ----------------- -The ``__ repository +The ``__ repository includes source code for a sample GPU compute workload, ``vcopy.cpp``. A copy of this file is available in the ``share/sample`` subdirectory after a normal -Omniperf installation, or via the ``$OMNIPERF_SHARE/sample`` directory when +ROCm Compute Profiler installation, or via the ``$ROCPROFCOMPUTE_SHARE/sample`` directory when using the supplied modulefile. The examples in this section use a compiled version of the ``vcopy`` workload to -demonstrate the use of Omniperf in MI accelerator performance analysis. Unless +demonstrate the use of ROCm Compute Profiler in MI accelerator performance analysis. Unless otherwise noted, the performance analysis is done on the :ref:`MI200 platform `. @@ -54,7 +54,7 @@ Workload compilation The following example demonstrates compilation of ``vcopy``. -.. code-block:: shell +.. code-block:: shell-session $ hipcc vcopy.cpp -o vcopy $ ls @@ -74,20 +74,20 @@ The following example demonstrates compilation of ``vcopy``. The following sample command profiles the ``vcopy`` workload. -.. code-block:: shell +.. code-block:: shell-session - $ omniperf profile --name vcopy -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile --name vcopy -- ./vcopy -n 1048576 -b 256 - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| - Omniperf version: 2.0.0 + rocprofiler-compute version: 2.0.0 Profiler choice: rocprofv1 - Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 Target: MI200 Command: ./vcopy -n 1048576 -b 256 Kernel Selection: None @@ -98,10 +98,10 @@ The following sample command profiles the ``vcopy`` workload. Collecting Performance Counters ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - [profiling] Current input file: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt - |-> [rocprof] RPL: on '240312_174329' from '/opt/rocm-5.2.1' in '/home/auser/repos/omniperf/src/omniperf' + [profiling] Current input file: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt + |-> [rocprof] RPL: on '240312_174329' from '/opt/rocm-5.2.1' in '/home/auser/repos/rocprofiler-compute/src/rocprof-compute' |-> [rocprof] RPL: profiling '""./vcopy -n 1048576 -b 256""' - |-> [rocprof] RPL: input file '/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt' + |-> [rocprof] RPL: input file '/home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_IFETCH_LEVEL.txt' |-> [rocprof] RPL: output dir '/tmp/rpl_data_240312_174329_692890' |-> [rocprof] RPL: result dir '/tmp/rpl_data_240312_174329_692890/input0_results_240312_174329' |-> [rocprof] ROCProfiler: input from "/tmp/rpl_data_240312_174329_692890/input0.xml" @@ -123,13 +123,13 @@ The following sample command profiles the ``vcopy`` workload. |-> [rocprof] Releasing CPU memory |-> [rocprof] |-> [rocprof] ROCPRofiler: 1 contexts collected, output directory /tmp/rpl_data_240312_174329_692890/input0_results_240312_174329 - |-> [rocprof] File '/home/auser/repos/omniperf/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv' is generating + |-> [rocprof] File '/home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/SQ_IFETCH_LEVEL.csv' is generating |-> [rocprof] - [profiling] Current input file: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200/perfmon/SQ_INST_LEVEL_LDS.txt + [profiling] Current input file: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200/perfmon/SQ_INST_LEVEL_LDS.txt ... - [roofline] Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + [roofline] Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 [roofline] No roofline data found. Generating... Empirical Roofline Calculation Copyright © 2022 Advanced Micro Devices, Inc. All rights reserved. @@ -171,9 +171,9 @@ The following sample command profiles the ``vcopy`` workload. .. _profiling-routine: -Notice the two main stages in Omniperf's *default* profiling routine. +Notice the two main stages in ROCm Compute Profiler's *default* profiling routine. -1. The first stage collects all the counters needed for Omniperf analysis +1. The first stage collects all the counters needed for ROCm Compute Profiler analysis (omitting any filters you have provided). 2. The second stage collects data for the roofline analysis (this stage can be @@ -187,7 +187,7 @@ example: * "MI200" for the AMD Instinct MI200 family of accelerators * "MI100" for the AMD Instinct MI100 family of accelerators -The SoC names are generated as a part of Omniperf, and do not *always* +The SoC names are generated as a part of ROCm Compute Profiler, and do not *always* distinguish between different accelerators in the same family; for instance, an Instinct MI210 vs an Instinct MI250. @@ -198,7 +198,7 @@ an Instinct MI210 vs an Instinct MI250. profiling output is stored in ``log.txt``. Roofline-specific benchmark results are stored in ``roofline.csv``. -.. code-block:: shell +.. code-block:: shell-session $ ls workloads/vcopy/MI200/ total 112 @@ -222,8 +222,8 @@ Filtering To reduce profiling time and the counters collected, you should use profiling filters. Profiling filters and their functionality depend on the underlying -profiler being used. While Omniperf is profiler-agnostic, this following is a -detailed description of profiling filters available when using Omniperf with +profiler being used. While ROCm Compute Profiler is profiler-agnostic, this following is a +detailed description of profiling filters available when using ROCm Compute Profiler with :doc:`ROCProfiler `. Filtering options @@ -255,7 +255,7 @@ Hardware component filtering ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ You can profile specific hardware components to speed up the profiling process. -In Omniperf, the term hardware block to refers to a hardware component or a +In ROCm Compute Profiler, the term hardware block to refers to a hardware component or a group of hardware components. All profiling results are accumulated in the same target directory without overwriting those for other hardware components. This enables incremental profiling and analysis. @@ -263,16 +263,16 @@ enables incremental profiling and analysis. The following example only gathers hardware counters for the shader sequencer (SQ) and L2 cache (TCC) components, skipping all other hardware components. -.. code-block:: shell +.. code-block:: shell-session - $ omniperf profile --name vcopy -b SQ TCC -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile --name vcopy -b SQ TCC -- ./vcopy -n 1048576 -b 256 - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| fname: pmc_cpc_perf: Skipped fname: pmc_spi_perf: Skipped @@ -289,9 +289,9 @@ The following example only gathers hardware counters for the shader sequencer fname: pmc_sqc_perf1: Skipped fname: pmc_sq_perf6: Added fname: pmc_sq_perf2: Added - Omniperf version: 2.0.0 + rocprofiler-compute version: 2.0.0 Profiler choice: rocprofv1 - Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 Target: MI200 Command: ./vcopy -n 1048576 -b 256 Kernel Selection: None @@ -314,20 +314,20 @@ kernel name substring list to isolate desired kernels. The following example demonstrates profiling isolating the kernel matching substring ``vecCopy``. -.. code-block:: shell +.. code-block:: shell-session - $ omniperf profile --name vcopy -k vecCopy -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile --name vcopy -k vecCopy -- ./vcopy -n 1048576 -b 256 - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| - Omniperf version: 2.0.0 + rocprofiler-compute version: 2.0.0 Profiler choice: rocprofv1 - Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 Target: MI200 Command: ./vcopy -n 1048576 -b 256 Kernel Selection: ['vecCopy'] @@ -349,20 +349,20 @@ Dispatch filtering is based on the *global* dispatch index of kernels in a run. The following example profiles only the first kernel dispatch in the execution of the application (note zero-based indexing). -.. code-block:: shell +.. code-block:: shell-session - $ omniperf profile --name vcopy -d 0 -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile --name vcopy -d 0 -- ./vcopy -n 1048576 -b 256 - ___ _ __ - / _ \ _ __ ___ _ __ (_)_ __ ___ _ __ / _| - | | | | '_ ` _ \| '_ \| | '_ \ / _ \ '__| |_ - | |_| | | | | | | | | | | |_) | __/ | | _| - \___/|_| |_| |_|_| |_|_| .__/ \___|_| |_| - |_| + __ _ + _ __ ___ ___ _ __ _ __ ___ / _| ___ ___ _ __ ___ _ __ _ _| |_ ___ + | '__/ _ \ / __| '_ \| '__/ _ \| |_ _____ / __/ _ \| '_ ` _ \| '_ \| | | | __/ _ \ + | | | (_) | (__| |_) | | | (_) | _|_____| (_| (_) | | | | | | |_) | |_| | || __/ + |_| \___/ \___| .__/|_| \___/|_| \___\___/|_| |_| |_| .__/ \__,_|\__\___| + |_| |_| - Omniperf version: 2.0.0 + rocprofiler-compute version: 2.0.0 Profiler choice: rocprofv1 - Path: /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Path: /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 Target: MI200 Command: ./vcopy -n 1048576 -b 256 Kernel Selection: None @@ -408,14 +408,14 @@ Roofline only The following example demonstrates profiling roofline data only: -.. code-block:: shell +.. code-block:: shell-session - $ omniperf profile --name vcopy --roof-only -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile --name vcopy --roof-only -- ./vcopy -n 1048576 -b 256 ... - [roofline] Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + [roofline] Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 [roofline] No roofline data found. Generating... - Checking for roofline.csv in /home/auser/repos/omniperf/sample/workloads/vcopy/MI200 + Checking for roofline.csv in /home/auser/repos/rocprofiler-compute/sample/workloads/vcopy/MI200 Empirical Roofline Calculation Copyright © 2022 Advanced Micro Devices, Inc. All rights reserved. Total detected GPU devices: 4 @@ -427,7 +427,7 @@ The following example demonstrates profiling roofline data only: An inspection of our workload output folder shows ``.pdf`` plots were generated successfully. -.. code-block:: shell +.. code-block:: shell-session $ ls workloads/vcopy/MI200/ total 48 @@ -441,7 +441,7 @@ successfully. .. note:: - Omniperf generates two roofline outputs to organize results and reduce + ROCm Compute Profiler generates two roofline outputs to organize results and reduce clutter. One chart plots FP32/FP64 performance while the other plots I8/FP16 performance. @@ -450,6 +450,6 @@ plot. .. image:: ../../data/profile/sample-roof-plot.png :align: center - :alt: Sample Omniperf roofline output + :alt: Sample ROCm Compute Profiler roofline output :width: 800 diff --git a/docs/how-to/use.rst b/docs/how-to/use.rst index 7377dd9f9..c3ecc9417 100644 --- a/docs/how-to/use.rst +++ b/docs/how-to/use.rst @@ -1,13 +1,13 @@ .. meta:: - :description: Omniperf basic usage - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: ROCm Compute Profiler basic usage + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, basics, usage, operations *********** Basic usage *********** -The following section outlines basic Omniperf workflows, modes, options, and +The following section outlines basic ROCm Compute Profiler workflows, modes, options, and operations. Command line profiler @@ -18,7 +18,7 @@ Launch and profile the target application using the command line profiler. The command line profiler launches the target application, calls the ROCProfiler API via the ``rocprof`` binary, and collects profile results for the specified kernels, dispatches, and hardware components. If not -specified, Omniperf defaults to collecting all available counters for all +specified, ROCm Compute Profiler defaults to collecting all available counters for all kernels and dispatches launched by the your executable. To collect the default set of data for all kernels in the target @@ -26,7 +26,7 @@ application, launch, for example: .. code-block:: shell - $ omniperf profile -n vcopy_data -- ./vcopy -n 1048576 -b 256 + $ rocprof-compute profile -n vcopy_data -- ./vcopy -n 1048576 -b 256 This runs the app, launches each kernel, and generates profiling results. By default, results are written to a subdirectory with your accelerator's name; @@ -35,7 +35,7 @@ via the ``-n`` argument. .. note:: - To collect all requested profile information, Omniperf might replay kernels + To collect all requested profile information, ROCm Compute Profiler might replay kernels multiple times. .. _basic-filter-data-collection: @@ -67,7 +67,7 @@ argument: .. code-block:: shell - $ omniperf analyze --list-metrics + $ rocprof-compute analyze --list-metrics .. _basic-analyze-cli: @@ -87,7 +87,7 @@ To interact with profiling results from a different session, provide the workload path. ``-p``, ``--path`` - Enables you to analyze existing profiling data in the Omniperf CLI. + Enables you to analyze existing profiling data in the ROCm Compute Profiler CLI. See :doc:`analyze/cli` for more detailed information. @@ -97,16 +97,16 @@ Analyze in the Grafana GUI -------------------------- To conduct a more in-depth analysis of profiling results, it's suggested to use -a Grafana GUI with Omniperf. To interact with profiling results, import your -data to the MongoDB instance included in the Omniperf Dockerfile. See +a Grafana GUI with ROCm Compute Profiler. To interact with profiling results, import your +data to the MongoDB instance included in the ROCm Compute Profiler Dockerfile. See :doc:`/install/grafana-setup`. -To interact with Grafana data, stored in the Omniperf database, enter +To interact with Grafana data, stored in the ROCm Compute Profiler database, enter ``database`` :ref:`mode `; for example: .. code-block:: shell - $ omniperf database --import [CONNECTION OPTIONS] + $ rocprof-compute database --import [CONNECTION OPTIONS] See :doc:`/how-to/analyze/grafana-gui` for more detailed information. @@ -115,7 +115,7 @@ See :doc:`/how-to/analyze/grafana-gui` for more detailed information. Modes ===== -Modes change the fundamental behavior of the Omniperf command line tool. +Modes change the fundamental behavior of the ROCm Compute Profiler command line tool. Depending on which mode you choose, different command line options become available. @@ -133,10 +133,10 @@ Profile mode .. code-block:: shell - $ omniperf profile --help + $ rocprof-compute profile --help See :doc:`profile/mode` to learn about this mode in depth and to get started -profiling with Omniperf. +profiling with ROCm Compute Profiler. .. _modes-analyze: @@ -144,24 +144,24 @@ Analyze mode ------------ ``analyze`` - Loads profiling data from the ``--path`` (``-p``) directory into the Omniperf + Loads profiling data from the ``--path`` (``-p``) directory into the ROCm Compute Profiler CLI analyzer where you have immediate access to profiling results and generated metrics. It generates metrics from the entirety of your profiled - application or a subset identified through the Omniperf CLI analysis filters. + application or a subset identified through the ROCm Compute Profiler CLI analysis filters. To generate a lightweight GUI interface, you can add the ``--gui`` flag to your analysis command. - This mode is a middle ground to the highly detailed Omniperf Grafana GUI and + This mode is a middle ground to the highly detailed ROCm Compute Profiler Grafana GUI and is great if you want immediate access to a hardware component you’re already familiar with. .. code-block:: shell - $ omniperf analyze --help + $ rocprof-compute analyze --help See :doc:`analyze/mode` to learn about this mode in depth and to get started -with analysis using Omniperf. +with analysis using ROCm Compute Profiler. .. _modes-database: @@ -178,7 +178,7 @@ Database mode .. code-block:: shell - $ omniperf database --help + $ rocprof-compute database --help See :doc:`/install/grafana-setup` to learn about setting up a Grafana server and database instance to make your profiling data more digestible and shareable. @@ -188,11 +188,11 @@ database instance to make your profiling data more digestible and shareable. Global options ============== -The Omniperf command line tool has a set of *global* utility options that are +The ROCm Compute Profiler command line tool has a set of *global* utility options that are available across all modes. ``-v``, ``--version`` - Prints the Omniperf version and exits. + Prints the ROCm Compute Profiler version and exits. ``-V``, ``--verbose`` Increases output verbosity. Use multiple times for higher levels of @@ -206,7 +206,7 @@ available across all modes. .. note:: - Omniperf also recognizes the project variable, ``OMNIPERF_COLOR`` should you + ROCm Compute Profiler also recognizes the project variable, ``ROCPROFCOMPUTE_COLOR`` should you choose to disable colorful output. To disable default colorful behavior, set this variable to ``0``. @@ -215,7 +215,7 @@ available across all modes. Basic operations ================ -The following table lists Omniperf's basic operations, their +The following table lists ROCm Compute Profiler's basic operations, their :ref:`modes `, and required arguments. .. list-table:: diff --git a/docs/index.rst b/docs/index.rst index 1df329e7d..80cd512bb 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -1,34 +1,34 @@ .. meta:: - :description: Omniperf documentation and reference + :description: ROCm Compute Profiler documentation and reference :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD -********************** -Omniperf documentation -********************** +*********************************** +ROCm Compute Profiler documentation +*********************************** -Omniperf documentation provides a comprehensive overview of Omniperf. -In addition to a full deployment guide with installation instructions, this -documentation also explains the ideas motivating the design behind the tool and -its components. +This documentation provides a comprehensive overview of the ROCm Compute +Profiler tool. In addition to a full deployment guide with installation +instructions, this documentation also explains the ideas motivating the design +behind the tool and its components. -If you're new to Omniperf, familiarize yourself with the tool by reviewing the +If you're new to ROCm Compute Profiler, familiarize yourself with the tool by reviewing the chapters that follow and gradually learn its more advanced features. To get -started, see :doc:`What is Omniperf? `. +started, see :doc:`What is ROCm Compute Profiler? `. -Omniperf is open source and hosted at ``__. +ROCm Compute Profiler is open source and hosted at ``__. .. grid:: 2 :gutter: 3 .. grid-item-card:: Install - * :doc:`install/core-install` - * :doc:`Grafana server for Omniperf ` + * :doc:`Installation and deployment ` + * :doc:`Grafana server for ROCm Compute Profiler ` .. grid-item:: -Use the following topics to learn more about the advantages of Omniperf in your -development toolkit, how it aims to model performance, and how to use Omniperf +Use the following topics to learn more about the advantages of ROCm Compute Profiler in your +development toolkit, how it aims to model performance, and how to use ROCm Compute Profiler in practice. .. grid:: 2 diff --git a/docs/install/core-install.rst b/docs/install/core-install.rst index 1d28b07b5..12985b4e9 100644 --- a/docs/install/core-install.rst +++ b/docs/install/core-install.rst @@ -1,15 +1,15 @@ .. meta:: - :description: Omniperf installation and deployment - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: ROCm Compute Profiler installation and deployment + :keywords: Omniperf, ROCm Compute Profiler, ROCm, tool, Instinct, accelerator, AMD, install, deploy, Grafana, client, configuration, modulefiles -********************************* -Installing and deploying Omniperf -********************************* +********************************************** +Installing and deploying ROCm Compute Profiler +********************************************** -Omniperf consists of two installation components. +ROCm Compute Profiler consists of two installation components. -* :ref:`Omniperf core installation ` (client-side) +* :ref:`ROCm Compute Profiler core installation ` (client-side) * Provides the core application profiling capability. * Allows the collection of performance counters, filtering by hardware @@ -17,18 +17,18 @@ Omniperf consists of two installation components. * Provides a CLI-based analysis mode. * Provides a standalone web interface for importing analysis metrics. -* :doc:`Grafana server for Omniperf ` (server-side) (*optional*) +* :doc:`Grafana server for ROCm Compute Profiler ` (server-side) (*optional*) * Hosts the MongoDB backend and Grafana instance. * Is packaged in a Docker container for easy setup. Determine what you need to install based on how you would like to interact with -Omniperf. See the following decision tree to help determine what installation is +ROCm Compute Profiler. See the following decision tree to help determine what installation is right for you. .. image:: ../data/install/install-decision-tree.png :align: center - :alt: Decision tree for installing and deploying Omniperf + :alt: Decision tree for installing and deploying ROCm Compute Profiler :width: 800 .. _core-install: @@ -36,20 +36,26 @@ right for you. Core installation ================= -The core Omniperf application requires the following basic software -dependencies. As of ROCm 6.2, the core Omniperf is included with your ROCm +The core ROCm Compute Profiler application requires the following basic software +dependencies. As of ROCm 6.2, the core ROCm Compute Profiler is included with your ROCm installation. * Python ``>= 3.8`` * CMake ``>= 3.19`` * ROCm ``>= 5.7.1`` -Omniperf depends on a number of Python packages documented in the top-level -``requirements.txt`` file. Install these *before* configuring Omniperf. +.. note:: + + ROCm Compute Profiler will use the first version of ``python3`` found in your system's + ``PATH``. If the default version of Python is older than 3.8, you may need to + update your system's ``PATH`` to point to a newer version. + +ROCm Compute Profiler depends on a number of Python packages documented in the top-level +``requirements.txt`` file. Install these *before* configuring ROCm Compute Profiler. .. tip:: - If looking to build Omniperf as a developer, consider these additional + If looking to build ROCm Compute Profiler as a developer, consider these additional requirements. .. list-table:: @@ -58,14 +64,24 @@ Omniperf depends on a number of Python packages documented in the top-level - Python packages required to build this documentation from source. * - ``requirements-test.txt`` - - Python packages required to run Omniperf's CI suite using PyTest. + - Python packages required to run ROCm Compute Profiler's CI suite using PyTest. -The recommended procedure for Omniperf usage is to install into a shared file +The recommended procedure for ROCm Compute Profiler usage is to install into a shared file system so that multiple users can access the final installation. The following steps illustrate how to install the necessary Python dependencies -using `pip `_ and Omniperf into a +using `pip `_ and ROCm Compute Profiler into a shared location controlled by the ``INSTALL_DIR`` environment variable. +.. tip:: + + To always run ROCm Compute Profiler with a particular version of Python, you can create a + bash alias. For example, to run ROCm Compute Profiler with Python 3.10, you can run the + following command: + + .. code-block:: shell + + alias rocprof-compute-mypython="/usr/bin/python3.10 /opt/rocm/bin/rocprof-compute" + .. _core-install-cmake-vars: Configuration variables @@ -81,13 +97,13 @@ follows. - Description * - ``CMAKE_INSTALL_PREFIX`` - - Controls the install path for Omniperf files. + - Controls the install path for ROCm Compute Profiler files. * - ``PYTHON_DEPS`` - Specifies an optional path to resolve Python package dependencies. * - ``MOD_INSTALL_PATH`` - - Specifies an optional path for separate Omniperf modulefile installation. + - Specifies an optional path for separate ROCm Compute Profiler modulefile installation. .. _core-install-steps: @@ -95,20 +111,20 @@ Install from source ------------------- #. A typical install begins by downloading the latest release tarball available - from ``__. From there, untar and + from ``__. From there, untar and navigate into the top-level directory. .. - {{ config.version }} substitutes the Omniperf version in ../conf.py + {{ config.version }} substitutes the ROCm Compute Profiler version in ../conf.py .. datatemplate:nodata:: .. code-block:: shell - tar xfz omniperf-v{{ config.version }}.tar.gz - cd omniperf-v{{ config.version }} + tar xfz rocprofiler-compute-v{{ config.version }}.tar.gz + cd rocprofiler-compute-v{{ config.version }} -#. Next, install Python dependencies and complete the Omniperf configuration and +#. Next, install Python dependencies and complete the ROCm Compute Profiler configuration and install process. .. datatemplate:nodata:: @@ -121,12 +137,12 @@ Install from source # install python deps python3 -m pip install -t ${INSTALL_DIR}/python-libs -r requirements.txt - # configure Omniperf for shared install + # configure ROCm Compute Profiler for shared install mkdir build cd build cmake -DCMAKE_INSTALL_PREFIX=${INSTALL_DIR}/{{ config.version }} \ -DPYTHON_DEPS=${INSTALL_DIR}/python-libs \ - -DMOD_INSTALL_PATH=${INSTALL_DIR}/modulefiles .. + -DMOD_INSTALL_PATH=${INSTALL_DIR}/modulefiles/rocprofiler-compute .. # install make install @@ -153,33 +169,33 @@ Execution using modulefiles The installation process includes the creation of an environment modulefile for use with `Lmod `_. On systems that support Lmod, -you can register the Omniperf modulefile directory and setup your environment -for execution of Omniperf as follows. +you can register the ROCm Compute Profiler modulefile directory and setup your environment +for execution of ROCm Compute Profiler as follows. .. datatemplate:nodata:: .. code-block:: shell $ module use $INSTALL_DIR/modulefiles - $ module load omniperf - $ which omniperf - /opt/apps/omniperf/{{ config.version }}/bin/omniperf + $ module load rocprofiler-compute + $ which rocprof-compute + /opt/apps/rocprofiler-compute/{{ config.version }}/bin/rocprof-compute - $ omniperf --version + $ rocprof-compute --version ROC Profiler: /opt/rocm-5.1.0/bin/rocprof - omniperf (v{{ config.version }}) + rocprofiler-compute (v{{ config.version }}) .. tip:: If you're relying on an Lmod Python module locally, you may wish to customize - the resulting Omniperf modulefile post-installation to include extra + the resulting ROCm Compute Profiler modulefile post-installation to include extra module dependencies. Execution without modulefiles ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -To use Omniperf without the companion modulefile, update your ``PATH`` +To use ROCm Compute Profiler without the companion modulefile, update your ``PATH`` settings to enable access to the command line binary. If you installed Python dependencies in a shared location, also update your ``PYTHONPATH`` configuration. @@ -196,7 +212,7 @@ configuration. Install via package manager --------------------------- -Once ROCm (minimum version 6.2.0) is installed, you can install Omniperf using +Once ROCm (minimum version 6.2.0) is installed, you can install ROCm Compute Profiler using your operating system's native package manager using the following commands. See :doc:`rocm-install-on-linux:index` for guidance on installing the ROCm software stack. @@ -207,29 +223,38 @@ software stack. .. code-block:: shell - $ sudo apt install omniperf - $ pip install -r /opt/rocm/libexec/omniperf/requirements.txt + $ sudo apt install rocprofiler-compute + # Include rocprofiler-compute in your system PATH + $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0 + # Install Python dependencies + $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt .. tab-item:: Red Hat Enterprise Linux .. code-block:: shell - $ sudo dnf install omniperf - $ pip install -r /opt/rocm/libexec/omniperf/requirements.txt + $ sudo dnf install rocprofiler-compute + # Include rocprofiler-compute in your system PATH + $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0 + # Install Python dependencies + $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt .. tab-item:: SUSE Linux Enterprise Server .. code-block:: shell - $ sudo zypper install omniperf - $ pip install -r /opt/rocm/libexec/omniperf/requirements.txt + $ sudo zypper install rocprofiler-compute + # Include rocprofiler-compute in your system PATH + $ sudo update-alternatives --install /usr/bin/rocprofiler-compute rocprof-compute /opt/rocm/bin/rocprofiler-compute 0 + # Install Python dependencies + $ python3 -m pip install -r /opt/rocm/libexec/rocprofiler-compute/requirements.txt .. _core-install-rocprof-var: ROCProfiler ----------- -Omniperf relies on :doc:`ROCProfiler `'s ``rocprof`` binary +ROCm Compute Profiler relies on :doc:`ROCProfiler `'s ``rocprof`` binary during the profiling process. Normally, the path to this binary is detected automatically, but you can override the path by the setting the optional ``ROCPROF`` environment variable. diff --git a/docs/install/grafana-setup.rst b/docs/install/grafana-setup.rst index a7486d286..00a653f15 100644 --- a/docs/install/grafana-setup.rst +++ b/docs/install/grafana-setup.rst @@ -1,26 +1,26 @@ .. meta:: - :description: Omniperf Grafana server installation and deployment - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: ROCm Compute Profiler Grafana server installation and deployment + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, install, deploy, Grafana, server, configuration, GUI -**************************************** -Setting up a Grafana server for Omniperf -**************************************** +*************************************************** +Setting up Grafana server for ROCm Compute Profiler +*************************************************** A Grafana server is *not required* to profile or analyze performance data from the CLI. It's a supplementary mechanism to help you import performance data and examine it in a detailed `Grafana `_ dashboard GUI. -Learn about installing and configuring the main Omniperf tool in +Learn about installing and configuring the main ROCm Compute Profiler tool in :ref:`core-install`. -Setting up a Grafana instance for Omniperf requires the following basic software +Setting up a Grafana instance for ROCm Compute Profiler requires the following basic software dependencies. * `Docker Engine `_ -The recommended process for enabling the server-side of Omniperf is to use the +The recommended process for enabling the server-side of ROCm Compute Profiler is to use the provided ``Dockerfile`` to build the Grafana and MongoDB instance. .. _grafana-mongodb-setup: @@ -34,7 +34,7 @@ the following setup instructions. Install MongoDB utilities ------------------------- -Omniperf uses the +ROCm Compute Profiler uses the `mongoimport `_ utility to upload data to your Grafana instance's backend database. @@ -70,7 +70,7 @@ crash or reset. This is called *creating a persistent volume*. Build and launch the Docker container ------------------------------------- -You're now ready to build your ``Dockerfile``. Navigate to your Omniperf install +You're now ready to build your ``Dockerfile``. Navigate to your ROCm Compute Profiler install directory to begin. .. code-block:: bash @@ -79,6 +79,13 @@ directory to begin. $ sudo docker-compose build $ sudo docker-compose up -d +.. note:: + + To troubleshoot Docker container build failures related to certificate verification, try + disabling any network proxy services on the host system. These proxy services can interfere + with OpenSSL's ability to retrieve a correct certificate chain when the container accesses + external websites. + The TCP ports for Grafana (``4000``) and MongoDB (``27017``) in the Docker container are mapped to ``14000`` and ``27018``, respectively, on the host side. @@ -158,12 +165,12 @@ connection is successful. .. _grafana-import-dashboard-file: -Import the Omniperf dashboard file ----------------------------------- +Import the ROCm Compute Profiler dashboard file +----------------------------------------------- From the **Create** → **Import** page, upload the dashboard file, ``/dashboards/Omniperf_v{__VERSION__}_pub.json`` from the -:doc:`Omniperf tarball `. +:doc:`ROCm Compute Profiler tarball `. Edit both the dashboard **Name** and the **Unique identifier (UID)** fields to uniquely identify the dashboard. Click **Import** to complete the process. @@ -177,18 +184,18 @@ uniquely identify the dashboard. Click **Import** to complete the process. .. _grafana-select-workload: -Select and load the Omniperf workload -------------------------------------- +Select and load the ROCm Compute Profiler workload +-------------------------------------------------- Once you have imported a dashboard you're ready to begin. Start by browsing available dashboards and selecting the dashboard you have just imported. .. figure:: ../data/install/opening_dashboard.png :align: center - :alt: Opening your Omniperf dashboard in Grafana + :alt: Opening your ROCm Compute Profiler dashboard in Grafana :width: 800 - Opening your Omniperf profiling dashboard in Grafana. + Opening your ROCm Compute Profiler profiling dashboard in Grafana. Remember that you need to upload workload data to the MongoDB backend before analyzing in your Grafana interface. See a detailed example of this in @@ -199,10 +206,10 @@ from the workload dropdown located at the top of your Grafana dashboard. .. figure:: ../data/install/grafana_workload_selection.png :align: center - :alt: Omniperf workload selection in Grafana + :alt: ROCm Compute Profiler workload selection in Grafana :width: 800 - Selecting your Omniperf workload in Grafana. + Selecting your ROCm Compute Profiler workload in Grafana. For more information on how to use the Grafana interface for analysis see :doc:`/how-to/analyze/grafana-gui`. diff --git a/docs/license.rst b/docs/license.rst index c423ed34f..b64c89729 100644 --- a/docs/license.rst +++ b/docs/license.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf license - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, + :description: ROCm Compute Profiler license + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD, license ******* diff --git a/docs/reference/compatible-accelerators.rst b/docs/reference/compatible-accelerators.rst index b93c72032..65a3f70a1 100644 --- a/docs/reference/compatible-accelerators.rst +++ b/docs/reference/compatible-accelerators.rst @@ -1,36 +1,36 @@ .. meta:: - :description: Omniperf support: compatible accelerators and GPUs - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, GPU + :description: ROCm Compute Profiler support: compatible accelerators and GPUs + :keywords: Omniperf, compatible, cdna, gcn, gfx, rdna, radeon, hardware, architecture *********************** Compatible accelerators *********************** The following table lists SoCs (System on Chip) tested for compatibility with -Omniperf. See :doc:`rocm:reference/gpu-arch-specs` for full AMD accelerator and +ROCm Compute Profiler. See :doc:`rocm:reference/gpu-arch-specs` for full AMD accelerator and GPU specifications. .. _def-soc: .. note:: - In Omniperf documentation, the term System on Chip (SoC) refers to a + In ROCm Compute Profiler documentation, the term System on Chip (SoC) refers to a particular family of AMD accelerators. .. list-table:: - :header-rows: 1 + :header-rows: 1 - * - Platform - - Status + * - Platform + - Status - * - AMD Instinct™ MI300 - - Supported ✅ + * - AMD Instinct™ MI300 + - Supported ✅ - * - AMD Instinct MI200 - - Supported ✅ + * - AMD Instinct MI200 + - Supported ✅ - * - AMD Instinct MI100 - - Supported ✅ + * - AMD Instinct MI100 + - Supported ✅ - * - AMD Instinct MI50, MI60 (Vega 20) - - No support ❌ + * - AMD Instinct MI50, MI60 (Vega 20) + - No support ❌ diff --git a/docs/reference/faq.rst b/docs/reference/faq.rst index 3cbbe778f..2ec10debf 100644 --- a/docs/reference/faq.rst +++ b/docs/reference/faq.rst @@ -1,6 +1,6 @@ .. meta:: - :description: Omniperf FAQ and troubleshooting - :keywords: Omniperf, FAQ, troubleshooting, ROCm, profiler, tool, Instinct, + :description: ROCm Compute Profiler FAQ and troubleshooting + :keywords: ROCm Compute Profiler, FAQ, troubleshooting, ROCm, profiler, tool, Instinct, accelerator, AMD, SSH, error, version, workaround, help *** @@ -9,8 +9,8 @@ FAQ Frequently asked questions and troubleshooting tips. -How do I export profiling data I have already generated using Omniperf? -======================================================================= +How do I export profiling data I have already generated using ROCm Compute Profiler? +==================================================================================== To interact with the Grafana GUI, you must sync data with the MongoDB backend. You can do this using :ref:`database ` mode. @@ -19,7 +19,7 @@ Pass in the directory of your desired workload as follows. .. code-block:: shell - $ omniperf database --import -w -H -u -t + $ rocprof-compute database --import -w -H -u -t python ast error: 'Constant' object has no attribute 'kind' =========================================================== diff --git a/docs/sphinx/_toc.yml.in b/docs/sphinx/_toc.yml.in index eb863b7a3..7df82fc8b 100644 --- a/docs/sphinx/_toc.yml.in +++ b/docs/sphinx/_toc.yml.in @@ -6,13 +6,14 @@ defaults: root: index subtrees: - entries: - - file: what-is-omniperf.rst + - file: what-is-rocprof-compute.rst - caption: Install entries: - file: install/core-install.rst + title: Installation and deployment - file: install/grafana-setup.rst - title: Grafana server for Omniperf + title: Grafana server setup - caption: How to entries: diff --git a/docs/sphinx/static/css/o_custom.css b/docs/sphinx/static/css/o_custom.css index a6cbe5718..b4fe010b5 100644 --- a/docs/sphinx/static/css/o_custom.css +++ b/docs/sphinx/static/css/o_custom.css @@ -1,30 +1,8 @@ -:root { - --amd-teal-500: #00C2DE; - --amd-teal-750: #00788E; -} - /* Override PyData Sphinx Theme default colors */ html[data-theme='light'] { - --pst-color-primary: var(--amd-teal-750); - --pst-color-primary-bg: var(--amd-teal-500); --pst-color-table-row-hover-bg: #E2E8F0; } html[data-theme='dark'] { - --pst-color-primary: var(--amd-teal-500); - --pst-color-primary-bg: var(--amd-teal-750); --pst-color-table-row-hover-bg: #1E293B; } - -html[data-theme='light'], -html[data-theme='dark'] { - --pst-color-link: var(--pst-color-primary); -} - -a svg { - color: var(--pst-color-text-base); -} - -a svg:hover { - color: var(--pst-color-link-hover); -} diff --git a/docs/tutorial/includes/infinity-fabric-transactions.rst b/docs/tutorial/includes/infinity-fabric-transactions.rst index fd510bd49..9e26e59bd 100644 --- a/docs/tutorial/includes/infinity-fabric-transactions.rst +++ b/docs/tutorial/includes/infinity-fabric-transactions.rst @@ -5,7 +5,7 @@ Infinity Fabric transactions For this example, consider the :dev-sample:`Infinity Fabric™ sample ` distributed as a part of - Omniperf. + ROCm Compute Profiler. This following code snippet launches a simple read-only kernel. @@ -36,7 +36,7 @@ is identically false -- and thus we expect no writes. .. note:: - The actual sample included with Omniperf also includes the ability to select + The actual sample included with ROCm Compute Profiler also includes the ability to select different operation types (such as atomics, writes). This abbreviated version is presented here for reference only. @@ -44,13 +44,13 @@ Finally, this sample code lets the user control the :ref:`granularity of an allocation `, the owner of an allocation (local HBM, CPU DRAM or remote HBM), and the size of an allocation (the default is :math:`\sim4`\ GiB) via command line arguments. In doing so, we can explore -the impact of these parameters on the L2-Fabric metrics reported by Omniperf to +the impact of these parameters on the L2-Fabric metrics reported by ROCm Compute Profiler to further understand their meaning. .. note:: All results in this section were generated an a node of Infinity - Fabric connected MI250 accelerators using ROCm version 5.6.0, and Omniperf + Fabric connected MI250 accelerators using ROCm version 5.6.0, and ROCm Compute Profiler version 2.0.0. Although results may vary with ROCm versions and accelerator connectivity, we expect the lessons learned here to be broadly applicable. @@ -64,7 +64,7 @@ In our first experiment, we consider the simplest possible case, a .. code-block:: shell-session - $ omniperf profile -n coarse_grained_local --no-roof -- ./fabric -t 1 -o 0 + $ rocprof-compute profile -n coarse_grained_local --no-roof -- ./fabric -t 1 -o 0 Using: mtype:CoarseGrained mowner:Device @@ -73,7 +73,7 @@ In our first experiment, we consider the simplest possible case, a mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/coarse_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/coarse_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -163,7 +163,7 @@ accelerator. Our code uses the ``hipExtMallocWithFlag`` API with the .. code-block:: shell-session - $ omniperf profile -n fine_grained_local --no-roof -- ./fabric -t 0 -o 0 + $ rocprof-compute profile -n fine_grained_local --no-roof -- ./fabric -t 0 -o 0 Using: mtype:FineGrained mowner:Device @@ -172,7 +172,7 @@ accelerator. Our code uses the ``hipExtMallocWithFlag`` API with the mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/fine_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/fine_grained_local/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -245,7 +245,7 @@ substantial change in the L2-Fabric metrics: .. code-block:: shell-session - $ omniperf profile -n fine_grained_remote --no-roof -- ./fabric -t 0 -o 2 + $ rocprof-compute profile -n fine_grained_remote --no-roof -- ./fabric -t 0 -o 2 Using: mtype:FineGrained mowner:Remote @@ -254,7 +254,7 @@ substantial change in the L2-Fabric metrics: mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/fine_grained_remote/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/fine_grained_remote/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -339,7 +339,7 @@ fine-grained memory using the ``hipHostMalloc`` API: .. code-block:: shell-session - $ omniperf profile -n fine_grained_host --no-roof -- ./fabric -t 0 -o 1 + $ rocprof-compute profile -n fine_grained_host --no-roof -- ./fabric -t 0 -o 1 Using: mtype:FineGrained mowner:Host @@ -348,7 +348,7 @@ fine-grained memory using the ``hipHostMalloc`` API: mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/fine_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/fine_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -416,7 +416,7 @@ allocation as coarse-grained: .. code-block:: shell-session - $ omniperf profile -n coarse_grained_host --no-roof -- ./fabric -t 1 -o 1 + $ rocprof-compute profile -n coarse_grained_host --no-roof -- ./fabric -t 1 -o 1 Using: mtype:CoarseGrained mowner:Host @@ -425,7 +425,7 @@ allocation as coarse-grained: mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/coarse_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/coarse_grained_host/mi200 -b 17.2.0 17.2.1 17.2.2 17.2.3 17.4.0 17.4.1 17.4.2 17.5.0 17.5.1 17.5.2 17.5.3 17.5.4 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -484,7 +484,7 @@ operations to fine-grained memory allocated on the host: .. code-block:: shell-session - $ omniperf profile -n fine_grained_host_write --no-roof -- ./fabric -t 0 -o 1 -p 1 + $ rocprof-compute profile -n fine_grained_host_write --no-roof -- ./fabric -t 0 -o 1 -p 1 Using: mtype:FineGrained mowner:Host @@ -493,7 +493,7 @@ operations to fine-grained memory allocated on the host: mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/fine_grained_host_writes/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/fine_grained_host_writes/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions @@ -576,7 +576,7 @@ operations to the CPU’s DRAM. .. code-block:: shell-session - $ omniperf profile -n fine_grained_host_add --no-roof -- ./fabric -t 0 -o 1 -p 2 + $ rocprof-compute profile -n fine_grained_host_add --no-roof -- ./fabric -t 0 -o 1 -p 2 Using: mtype:FineGrained mowner:Host @@ -585,7 +585,7 @@ operations to the CPU’s DRAM. mdata:Unsigned remoteId:-1 <...> - $ omniperf analyze -p workloads/fine_grained_host_add/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2 + $ rocprof-compute analyze -p workloads/fine_grained_host_add/mi200 -b 17.2.4 17.2.5 17.2.6 17.2.7 17.2.8 17.4.3 17.4.4 17.4.5 17.4.6 17.5.5 17.5.6 17.5.7 17.5.8 17.5.9 17.5.10 -n per_kernel --dispatch 2 <...> 17. L2 Cache 17.2 L2 - Fabric Transactions diff --git a/docs/tutorial/includes/instructions-per-cycle-and-utilizations.rst b/docs/tutorial/includes/instructions-per-cycle-and-utilizations.rst index dcbf37266..c9efe8502 100644 --- a/docs/tutorial/includes/instructions-per-cycle-and-utilizations.rst +++ b/docs/tutorial/includes/instructions-per-cycle-and-utilizations.rst @@ -5,7 +5,7 @@ Instructions-per-cycle and utilizations example For this example, consider the :dev-sample:`instructions-per-cycle (IPC) example ` included with -Omniperf. +ROCm Compute Profiler. This example is compiled using ``c++17`` support: @@ -17,7 +17,7 @@ and was run on an MI250 CDNA2 accelerator: .. code-block:: shell - $ omniperf profile -n ipc --no-roof -- ./ipc + $ rocprof-compute profile -n ipc --no-roof -- ./ipc The results shown in this section are *generally* applicable to CDNA accelerators, but may vary between generations and specific products. @@ -64,11 +64,11 @@ operation, i.e., a ``v_mov_b32`` instruction, e.g.: This instruction simply copies the contents from the source register (``v1``) to the destination register (``v0``). Investigating this kernel -with Omniperf, we see: +with ROCm Compute Profiler, we see: .. code-block:: shell-session - $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 7 -b 11.2 + $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 7 -b 11.2 <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -172,7 +172,7 @@ in the IPC example: .. code-block:: shell - $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 8 -b 11.2 --decimal 4 + $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 8 -b 11.2 --decimal 4 <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -240,7 +240,7 @@ instructions executed over the total There are further complications of the Issued IPC metric (**11.2.1**) that make its use more complicated. We will be explore that in the :ref:`following section `. For these reasons, - Omniperf typically promotes use of the regular IPC metric (**11.2.0**), e.g., in + ROCm Compute Profiler typically promotes use of the regular IPC metric (**11.2.0**), e.g., in the top-level Speed-of-Light chart. .. _ipc-internal-instructions: @@ -261,11 +261,11 @@ Here we choose to use the following no-op to make our point: s_nop 0x0 -Running this kernel through Omniperf yields: +Running this kernel through ROCm Compute Profiler yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 9 -b 11.2 + $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 9 -b 11.2 <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -362,11 +362,11 @@ operation, for instance: which, in analogue to our :ref:`v_mov ` example, copies the contents of the source scalar register (``s1``) to the destination -scalar register (``s0``). Running this kernel through Omniperf yields: +scalar register (``s0``). Running this kernel through ROCm Compute Profiler yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 10 -b 11.2 + $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 10 -b 11.2 <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -426,11 +426,11 @@ of our :ref:`v_mov ` example: That is, we wrap our :ref:`VALU ` operation inside a conditional where only one lane in our wavefront is active. Running this kernel -through Omniperf yields: +through ROCm Compute Profiler yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/ipc/mi200/ --dispatch 11 -b 11.2 + $ rocprof-compute analyze -p workloads/ipc/mi200/ --dispatch 11 -b 11.2 <...> -------------------------------------------------------------------------------- 0. Top Stat diff --git a/docs/tutorial/includes/lds-examples.rst b/docs/tutorial/includes/lds-examples.rst index f6cff7b72..8d1b7b1a9 100644 --- a/docs/tutorial/includes/lds-examples.rst +++ b/docs/tutorial/includes/lds-examples.rst @@ -4,22 +4,22 @@ LDS examples ============ For this example, consider the -:dev-sample:`LDS sample ` distributed as a part of Omniperf. This +:dev-sample:`LDS sample ` distributed as a part of ROCm Compute Profiler. This code contains two kernels to explore how both :doc:`LDS ` bandwidth and -bank conflicts are calculated in Omniperf. +bank conflicts are calculated in ROCm Compute Profiler. This example was compiled and run on an MI250 accelerator using ROCm -v5.6.0, and Omniperf v2.0.0. +v5.6.0, and ROCm Compute Profiler v2.0.0. .. code-block:: shell-session $ hipcc -O3 lds.hip -o lds -Finally, we generate our ``omniperf profile`` as: +Finally, we generate our ``rocprof-compute profile`` as: .. code-block:: shell-session - $ omniperf profile -n lds --no-roof -- ./lds + $ rocprof-compute profile -n lds --no-roof -- ./lds .. _lds-bandwidth: @@ -71,7 +71,7 @@ Next, let’s analyze the first of our bandwidth kernel dispatches: .. code-block:: shell - $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.1 --dispatch 0 -n per_kernel + $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.1 --dispatch 0 -n per_kernel <...> 12. Local Data Share (LDS) 12.2 LDS Stats @@ -93,7 +93,7 @@ Recall our definition of this metric: Here we see that this instruction *could* have loaded up to 256 bytes of data (4 bytes for each work-item in the wavefront), and therefore this -is the expected value for this metric in Omniperf, hence why this metric +is the expected value for this metric in ROCm Compute Profiler, hence why this metric is named the “theoretical” bandwidth. To further illustrate this point we plot the relationship of the @@ -104,11 +104,11 @@ launched from 1 to 256: .. figure:: ../data/profiling-by-example/ldsbandwidth.png :align: center :alt: Comparison of effective bandwidth versus the theoretical bandwidth - metric in Omniperf for our simple example. + metric in ROCm Compute Profiler for our simple example. :width: 800 Comparison of effective bandwidth versus the theoretical bandwidth - metric in Omniperf for our simple example. + metric in ROCm Compute Profiler for our simple example. Here we see that the theoretical bandwidth metric follows a step-function. It increases only when another wavefront issues an LDS instruction for up to 256 @@ -172,7 +172,7 @@ see: .. code-block:: shell - $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 256 -n per_kernel + $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 256 -n per_kernel <...> -------------------------------------------------------------------------------- 12. Local Data Share (LDS) @@ -196,7 +196,7 @@ Looking at the next ``conflicts`` dispatch (i.e., two work-items) yields: .. code-block:: shell - $ omniperf analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 257 -n per_kernel + $ rocprof-compute analyze -p workloads/lds/mi200/ -b 12.2.4 12.2.6 --dispatch 257 -n per_kernel <...> -------------------------------------------------------------------------------- 12. Local Data Share (LDS) diff --git a/docs/tutorial/includes/occupancy-limiters-example.rst b/docs/tutorial/includes/occupancy-limiters-example.rst index bd8129d12..dcbd6a61b 100644 --- a/docs/tutorial/includes/occupancy-limiters-example.rst +++ b/docs/tutorial/includes/occupancy-limiters-example.rst @@ -4,15 +4,15 @@ Occupancy limiters example ========================== For this example, consider the -:dev-sample:`occupancy ` included with Omniperf. We will +:dev-sample:`occupancy ` included with ROCm Compute Profiler. We will investigate the use of the resource allocation panel in the :ref:`Workgroup Manager `’s metrics section to determine occupancy limiters. This code contains several kernels to explore how both various kernel resources impact achieved occupancy, and how this is reported in -Omniperf. +ROCm Compute Profiler. This example was compiled and run on a MI250 accelerator using ROCm -v5.6.0, and Omniperf v2.0.0: +v5.6.0, and ROCm Compute Profiler v2.0.0: .. code-block:: shell @@ -21,11 +21,11 @@ v5.6.0, and Omniperf v2.0.0: We have again included the ``--save-temps`` flag to get the corresponding assembly. -Finally, we generate our Omniperf profile as: +Finally, we generate our ROCm Compute Profiler profile as: .. code-block:: shell - $ omniperf profile -n occupancy --no-roof -- ./occupancy + $ rocprof-compute profile -n occupancy --no-roof -- ./occupancy .. _occupancy-experiment-design: @@ -88,7 +88,7 @@ depend on the exact ROCm/compiler version. We will use various permutations of this kernel to limit occupancy, and more importantly for the purposes of this example, demonstrate how this -is reported in Omniperf. +is reported in ROCm Compute Profiler. .. _vgpr-occupancy: @@ -101,7 +101,7 @@ the analyze step on this kernel: .. code-block:: shell - $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 --dispatch 1 + $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 --dispatch 1 <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -226,7 +226,7 @@ Analyzing this: .. code-block:: shell - $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 --dispatch 3 + $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 --dispatch 3 <...> -------------------------------------------------------------------------------- 2. System Speed-of-Light @@ -351,7 +351,7 @@ Analyzing this workload yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 7.1.9 --dispatch 5 + $ rocprof-compute analyze -p workloads/occupancy/mi200/ -b 2.1.15 6.2 7.1.5 7.1.6 7.1.7 7.1.8 7.1.9 --dispatch 5 <...> -------------------------------------------------------------------------------- 0. Top Stat diff --git a/docs/tutorial/includes/valu-arithmetic-instruction-mix.rst b/docs/tutorial/includes/valu-arithmetic-instruction-mix.rst index 785fc6ecf..dcdb46ac4 100644 --- a/docs/tutorial/includes/valu-arithmetic-instruction-mix.rst +++ b/docs/tutorial/includes/valu-arithmetic-instruction-mix.rst @@ -5,7 +5,7 @@ VALU arithmetic instruction mix For this example, consider the :dev-sample:`instruction mix sample ` distributed as a part - of Omniperf. + of ROCm Compute Profiler. .. note:: @@ -55,7 +55,7 @@ Instruction mix ^^^^^^^^^^^^^^^ This example was compiled and run on a MI250 accelerator using ROCm - v5.6.0, and Omniperf v2.0.0. + v5.6.0, and ROCm Compute Profiler v2.0.0. .. code-block:: shell @@ -65,13 +65,13 @@ Generate the profile for this example using the following command. .. code-block:: shell - $ omniperf profile -n instmix --no-roof -- ./instmix + $ rocprof-compute profile -n instmix --no-roof -- ./instmix Analyze the instruction mix section. .. code-block:: shell - $ omniperf analyze -p workloads/instmix/mi200/ -b 10.2 + $ rocprof-compute analyze -p workloads/instmix/mi200/ -b 10.2 <...> 10. Compute Units - Instruction Mix 10.2 VALU Arithmetic Instr Mix diff --git a/docs/tutorial/includes/vector-memory-operation-counting.rst b/docs/tutorial/includes/vector-memory-operation-counting.rst index 2797ed8f2..4cfb875f4 100644 --- a/docs/tutorial/includes/vector-memory-operation-counting.rst +++ b/docs/tutorial/includes/vector-memory-operation-counting.rst @@ -10,7 +10,7 @@ Global / Generic (FLAT) For this example, consider the :dev-sample:`vector memory sample ` distributed as a part of -Omniperf. This code launches many different versions of a simple +ROCm Compute Profiler. This code launches many different versions of a simple read/write/atomic-only kernels targeting various address spaces. For example, below is our simple ``global_write`` kernel: @@ -24,7 +24,7 @@ below is our simple ``global_write`` kernel: .. note:: This example was compiled and run on an MI250 accelerator using ROCm - v5.6.0, and Omniperf v2.0.0. + v5.6.0, and ROCm Compute Profiler v2.0.0. .. code-block:: shell-session @@ -34,11 +34,11 @@ We have also chosen to include the ``--save-temps`` flag to save the compiler temporary files, such as the generated CDNA assembly code, for inspection. -Finally, we generate our ``omniperf profile`` as follows. +Finally, we generate our ``rocprof-compute profile`` as follows. .. code-block:: shell-session - $ omniperf profile -n vmem --no-roof -- ./vmem + $ rocprof-compute profile -n vmem --no-roof -- ./vmem .. _flat-experiment-design: @@ -94,7 +94,7 @@ First, we demonstrate our simple ``global_write`` kernel: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 1 -b 10.3 15.1.4 15.1.5 15.1.6 15.1.7 15.1.8 15.1.9 15.1.10 15.1.11 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 1 -b 10.3 15.1.4 15.1.5 15.1.6 15.1.7 15.1.8 15.1.9 15.1.10 15.1.11 -n per_kernel <...> -------------------------------------------------------------------------------- 0. Top Stat @@ -208,7 +208,7 @@ Examining this kernel in the VMEM Instruction Mix table yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 2 -b 10.3 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 2 -b 10.3 -n per_kernel <...> 0. Top Stat ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕ @@ -264,7 +264,7 @@ access. .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 2 -b 12.2.0 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 2 -b 12.2.0 -n per_kernel <...> 12. Local Data Share (LDS) 12.2 LDS Stats @@ -304,11 +304,11 @@ Here we observe a now familiar pattern: the compiler to statically eliminate, but is identically false. In this case, our ``main()`` function initializes the data in ``ptr`` to zero. -Running Omniperf on this kernel yields: +Running ROCm Compute Profiler on this kernel yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 3 -b 10.3 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 3 -b 10.3 -n per_kernel <...> 0. Top Stat ╒════╤════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕ @@ -383,11 +383,11 @@ false conditional (both ``zero`` and ``filter`` are set to zero in the kernel launch). Note that this is a *different* conditional from our pointer assignment (to avoid combination of the two). -Running Omniperf on this kernel reports: +Running ROCm Compute Profiler on this kernel reports: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 4 -b 10.3 12.2.0 16.3.10 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 4 -b 10.3 12.2.0 16.3.10 -n per_kernel <...> 0. Top Stat ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕ @@ -468,11 +468,11 @@ to a pointer. } -Running Omniperf on this kernel yields: +Running ROCm Compute Profiler on this kernel yields: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 5 -b 10.3 16.3.12 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 5 -b 10.3 16.3.12 -n per_kernel <...> 0. Top Stat ╒════╤══════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕ @@ -537,11 +537,11 @@ operation targets both LDS and global memory: This assigns every other work-item to atomically update global memory or local memory. -Running this kernel through Omniperf shows: +Running this kernel through ROCm Compute Profiler shows: .. code-block:: shell-session - $ omniperf analyze -p workloads/vmem/mi200/ --dispatch 6 -b 10.3 12.2.0 16.3.12 -n per_kernel + $ rocprof-compute analyze -p workloads/vmem/mi200/ --dispatch 6 -b 10.3 12.2.0 16.3.12 -n per_kernel <...> 0. Top Stat ╒════╤══════════════════════════════════════════╤═════════╤═══════════╤════════════╤══════════════╤════════╕ @@ -623,7 +623,7 @@ manner. See for further reading on this instruction type. We develop a `simple -kernel `__ +kernel `__ that uses stack memory: .. code-block:: cpp @@ -647,19 +647,19 @@ Our strategy here is to: to global memory to prevent the compiler from optimizing it out. This example was compiled and run on an MI250 accelerator using ROCm v5.6.0, and -Omniperf v2.0.0. +ROCm Compute Profiler v2.0.0. .. code-block:: shell-session $ hipcc -O3 stack.hip -o stack.hip -And profiled using Omniperf: +And profiled using ROCm Compute Profiler: .. code-block:: shell-session - $ omniperf profile -n stack --no-roof -- ./stack + $ rocprof-compute profile -n stack --no-roof -- ./stack <...> - $ omniperf analyze -p workloads/stack/mi200/ -b 10.3 16.3.11 -n per_kernel + $ rocprof-compute analyze -p workloads/stack/mi200/ -b 10.3 16.3.11 -n per_kernel <...> 10. Compute Units - Instruction Mix 10.3 VMEM Instr Mix diff --git a/docs/tutorial/learning-resources.rst b/docs/tutorial/learning-resources.rst index 931f1f7f1..7766e08dd 100644 --- a/docs/tutorial/learning-resources.rst +++ b/docs/tutorial/learning-resources.rst @@ -1,20 +1,22 @@ .. meta:: - :description: Omniperf external training resources - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD, - training, examples + :description: ROCm Compute Profiler external training resources + :keywords: Omniperf, examples, tutorials, videos, lesson, lessons, how ****************** Learning resources ****************** -This section is a catalog of external resources and third-party content that -can help you learn Omniperf. Some areas of the following content might be -outdated. +This section provides a curated list of external resources and third-party +content to support learning the ROCm Compute Profiler. Some information in +these materials may be outdated. -Introduction to Omniperf +ROCm Compute Profiler was previously known as Omniperf. Some of the following +resources use the earlier name. + +Introduction to ROCm Compute Profiler :fab:`youtube` `AMD profiling workshop (Pawsey Supercomputing Research Centre) `_ -Omniperf example exercises +ROCm Compute Profiler example exercises ``__ AMD Instinct™ tuning guides diff --git a/docs/tutorial/profiling-by-example.rst b/docs/tutorial/profiling-by-example.rst index e39239b9d..faa00b5ec 100644 --- a/docs/tutorial/profiling-by-example.rst +++ b/docs/tutorial/profiling-by-example.rst @@ -1,14 +1,14 @@ .. meta:: - :description: Omniperf: Profiling by example - :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD + :description: ROCm Compute Profiler: Profiling by example + :keywords: ROCm Compute Profiler, ROCm, profiler, tool, Instinct, accelerator, AMD ******************** Profiling by example ******************** The following examples refer to sample :doc:`HIP ` code located in -:fab:`github` :dev-sample:`ROCm/omniperf/blob/amd-mainline/sample <>` and distributed -as part of Omniperf. +:fab:`github` :dev-sample:`ROCm/rocprofiler-compute/blob/amd-mainline/sample <>` +and distributed as part of ROCm Compute Profiler. .. include:: ./includes/valu-arithmetic-instruction-mix.rst diff --git a/docs/what-is-omniperf.rst b/docs/what-is-rocprof-compute.rst similarity index 70% rename from docs/what-is-omniperf.rst rename to docs/what-is-rocprof-compute.rst index 473be896f..6c660097d 100644 --- a/docs/what-is-omniperf.rst +++ b/docs/what-is-rocprof-compute.rst @@ -1,33 +1,33 @@ .. meta:: - :description: What is Omniperf? + :description: What is ROCm Compute Profiler? :keywords: Omniperf, ROCm, profiler, tool, Instinct, accelerator, AMD -***************** -What is Omniperf? -***************** +****************************** +What is ROCm Compute Profiler? +****************************** -Omniperf is a kernel-level profiling tool for machine learning and high +ROCm Compute Profiler is a kernel-level profiling tool for machine learning and high performance computing (HPC) workloads running on AMD Instinct™ accelerators. AMD Instinct MI-series accelerators are data center-class GPUs designed for -compute and have some graphics capabilities disabled or removed. Omniperf -primarily targets use with +compute and have some graphics capabilities disabled or removed. +ROCm Compute Profiler primarily targets use with :doc:`accelerators in the MI300, MI200, and MI100 families `. Development is in progress to support Radeon™ (RDNA) GPUs. -Omniperf is built on top of :doc:`ROCProfiler ` to +ROCm Compute Profiler is built on top of :doc:`ROCProfiler ` to monitor hardware performance counters. .. _high-level-design: -High-level design of Omniperf -============================= +High-level design +================= -The architecture of Omniperf consists of three major components shown in the +The architecture of ROCm Compute Profiler consists of three major components shown in the following diagram. -Core Omniperf profiler ----------------------- +Core ROCm Compute Profiler +-------------------------- Acquires raw performance counters via application replay using ``rocprof``. Counters are stored in a comma-separated-values format for further @@ -35,43 +35,43 @@ Counters are stored in a comma-separated-values format for further micro-benchmarks to acquire hierarchical roofline data. The roofline model is not available on accelerators pre-MI200. -Grafana server for Omniperf ---------------------------- +Grafana server for ROCm Compute Profiler +---------------------------------------- * **Grafana database import**: All raw performance counters are imported into a :ref:`backend MongoDB database ` to support analysis and visualization in the Grafana GUI. Compatibility with - previously generated data using older Omniperf versions is not guaranteed. + previously generated data using older ROCm Compute Profiler versions is not guaranteed. * **Grafana analysis dashboard GUI**: The :doc:`Grafana dashboard ` retrieves the raw counters information from the backend database. It displays the relevant performance metrics and visualization. -Omniperf standalone GUI analyzer --------------------------------- +ROCm Compute Profiler standalone GUI analyzer +--------------------------------------------- -Omniperf provides a :doc:`standalone GUI ` to +ROCm Compute Profiler provides a :doc:`standalone GUI ` to enable basic performance analysis without the need to import data into a database instance. Find setup instructions in :doc:`install/grafana-setup` .. image:: data/install/omniperf_server_vs_client_install.png :align: center - :alt: Architectural design of Omniperf + :alt: Architectural design of ROCm Compute Profiler :width: 800 -Omniperf features -================= +Features +======== -Omniperf offers comprehensive profiling based on all available hardware counters +ROCm Compute Profiler offers comprehensive profiling based on all available hardware counters for the target accelerator. It delivers advanced performance analysis features, such as system Speed-of-Light (SOL) and hardware block-level SOL evaluations. -Additionally, Omniperf provides in-depth memory chart analysis, roofline +Additionally, ROCm Compute Profiler provides in-depth memory chart analysis, roofline analysis, baseline comparisons, and more, ensuring a thorough understanding of system performance. -Omniperf supports analysis through both the :doc:`command line ` or a -:doc:`GUI `. The following list describes Omniperf's features at a +ROCm Compute Profiler supports analysis through both the :doc:`command line ` or a +:doc:`GUI `. The following list describes ROCm Compute Profiler's features at a high level. * :doc:`Support for AMD Instinct MI300, MI200, and MI100 accelerators ` @@ -107,8 +107,8 @@ high level. * :ref:`Scalar L1D Cache panel ` - * :ref:`L1 Address Processing Unit, or, Texture Addresser (TA) ` - and :ref:`L1 Backend Data Processing Unit, or, Texture Data (TD) ` panels + * :ref:`L1 Address Processing Unit or Texture Addresser (TA) `; + and :ref:`L1 Backend Data Processing Unit or Texture Data (TD) ` panels * :ref:`Vector L1D Cache panel ` @@ -127,3 +127,4 @@ high level. * :ref:`Baseline comparisons ` * :ref:`Multiple normalizations ` +