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# Profile Mode
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```eval_rst
.. toctree::
:glob:
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:maxdepth: 5
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```
The [Omniperf](https://github.com/AMDResearch/omniperf) 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
`$OMNIPERF_SHARE/sample` directory when using the supplied modulefile.
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A compiled version of this workload is used throughout the following
sections to demonstrate the use of Omniperf in MI GPU performance
analysis. Unless otherwise noted, the performance analysis is done on
the MI200 platform.
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## Workload Compilation
**vcopy compilation:**
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```shell-session
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$ hipcc vcopy.cpp -o vcopy
$ ls
vcopy vcopy.cpp
$ ./vcopy 1048576 256
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Finished allocating vectors on the CPU
Finished allocating vectors on the GPU
Finished copying vectors to the GPU
sw thinks it moved 1.000000 KB per wave
Total threads: 1048576, Grid Size: 4096 block Size:256, Wavefronts:16384:
Launching the kernel on the GPU
Finished executing kernel
Finished copying the output vector from the GPU to the CPU
Releasing GPU memory
Releasing CPU memory
```
## Omniperf Profiling
The *omniperf* script, available through the Omniperf repository, is used to aquire all necessary performance monitoring data through analysis of compute workloads.
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**omniperf help:**
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```shell-session
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$ omniperf profile --help
ROC Profiler: /usr/bin/rocprof
usage:
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omniperf profile --name <workload_name> [profile options] [roofline options] -- <profile_cmd>
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-------------------------------------------------------------------------------
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Examples:
omniperf profile -n vcopy_all -- ./vcopy 1048576 256
omniperf profile -n vcopy_SPI_TCC -b SQ TCC -- ./vcopy 1048576 256
omniperf profile -n vcopy_kernel -k vecCopy -- ./vcopy 1048576 256
omniperf profile -n vcopy_disp -d 0 -- ./vcopy 1048576 256
omniperf profile -n vcopy_roof --roof-only -- ./vcopy 1048576 256
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-------------------------------------------------------------------------------
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Help:
-h, --help show this help message and exit
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General Options:
-v, --version show program's version number and exit
-V, --verbose Increase output verbosity
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Profile Options:
-n , --name Assign a name to workload.
-p , --path Specify path to save workload.
(DEFAULT: /home/colramos/GitHub/omniperf/workloads/<name>)
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-k [ ...], --kernel [ ...] Kernel filtering.
-b [ ...], --ipblocks [ ...] Hardware block filtering:
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SQ
SQC
TA
TD
TCP
TCC
SPI
CPC
CPF
-d [ ...], --dispatch [ ...] Dispatch ID filtering.
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--no-roof Profile without collecting roofline data.
-- [ ...] Provide command for profiling after double dash.
Standalone Roofline Options:
--roof-only Profile roofline data only.
--sort Overlay top kernels or top dispatches: (DEFAULT: kernels)
kernels
dispatches
-m , --mem-level Filter by memory level: (DEFAULT: ALL)
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HBM
L2
vL1D
LDS
--device GPU device ID. (DEFAULT: ALL)
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--kernel-names Include kernel names in roofline plot.
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```
- The `-k` \<kernel> flag allows for kernel filtering, which is compatible with the current rocProf utility.
- The `-d` \<dispatch> flag allows for dispatch ID filtering, which is compatible with the current rocProf utility.
- The `-b` \<ipblocks> allows system profiling on one or more selected hardware components to speed up the profiling process. One can gradually include more hardware components, without overwriting performance data acquired on other hardware components.
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The following sample command profiles the *vcopy* workload.
**vcopy profiling:**
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```shell-session
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$ omniperf profile --name vcopy -- ./vcopy 1048576 256
Resolving rocprof
ROC Profiler: /usr/bin/rocprof
-------------
Profile only
-------------
omniperf ver: 1.0.8-PR1
Path: /home/colramos/GitHub/omniperf-pub/workloads
Target: mi200
Command: /home/colramos/vcopy 1048576 256
Kernel Selection: None
Dispatch Selection: None
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IP Blocks: All
Log: /home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/log.txt
/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt
RPL: on '230411_165021' from '/opt/rocm-5.2.1' in '/home/colramos/GitHub/omniperf-pub'
RPL: profiling '""/home/colramos/vcopy 1048576 256""'
RPL: input file '/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt'
RPL: output dir '/tmp/rpl_data_230411_165021_26406'
RPL: result dir '/tmp/rpl_data_230411_165021_26406/input0_results_230411_165021'
Finished allocating vectors on the CPU
ROCProfiler: input from "/tmp/rpl_data_230411_165021_26406/input0.xml"
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gpu_index =
kernel =
range =
3 metrics
SQ_INSTS_SMEM, SQ_INST_LEVEL_SMEM, SQ_ACCUM_PREV_HIRES
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Finished allocating vectors on the GPU
Finished copying vectors to the GPU
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sw thinks it moved 1.000000 KB per wave
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Total threads: 1048576, Grid Size: 4096 block Size:256, Wavefronts:16384:
Launching the kernel on the GPU
Finished executing kernel
Finished copying the output vector from the GPU to the CPU
Releasing GPU memory
Releasing CPU memory
... ...
ROCPRofiler: 1 contexts collected, output directory /tmp/rpl_data_220527_130317_1787038/input_results_220527_130317
File 'workloads/vcopy/mi200/timestamps.csv' is generating
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Total detected GPU devices: 2
GPU Device 0: Profiling...
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
HBM BW, GPU ID: 0, workgroupSize:256, workgroups:2097152, experiments:100, traffic:8589934592 bytes, duration:6.2 ms, mean:1382.7 GB/sec, stdev=2.4 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
L2 BW, GPU ID: 0, workgroupSize:256, workgroups:8192, experiments:100, traffic:687194767360 bytes, duration:157.9 ms, mean:4358.7 GB/sec, stdev=4.7 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
L1 BW, GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, traffic:26843545600 bytes, duration:3.3 ms, mean:8247.1 GB/sec, stdev=5.1 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
LDS BW, GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, traffic:33554432000 bytes, duration:2.4 ms, mean:14246.3 GB/sec, stdev=29.5 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak FLOPs (FP32), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:274877906944, duration:14.507 ms, mean:18949.6 GFLOPS, stdev=4.5 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak FLOPs (FP64), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:137438953472, duration:7.5 ms, mean:18308.197266.1 GFLOPS, stdev=3.6 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (BF16), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:2147483648000, duration:14.0 ms, mean:153574.8 GFLOPS, stdev=79.9 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F16), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:2147483648000, duration:14.5 ms, mean:147680.1 GFLOPS, stdev=34.7 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F32), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:536870912000, duration:14.5 ms, mean:37142.1 GFLOPS, stdev=8.4 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F64), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, FLOP:268435456000, duration:7.3 ms, mean:36919.5 GFLOPS, stdev=14.1 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA IOPs (I8), GPU ID: 0, workgroupSize:256, workgroups:16384, experiments:100, IOP:2147483648000, duration:14.4 ms, mean:149570.6 GOPS, stdev=41.7 GOPS
GPU Device 1: Profiling...
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
HBM BW, GPU ID: 1, workgroupSize:256, workgroups:2097152, experiments:100, traffic:8589934592 bytes, duration:6.2 ms, mean:1382.7 GB/sec, stdev=2.9 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
L2 BW, GPU ID: 1, workgroupSize:256, workgroups:8192, experiments:100, traffic:687194767360 bytes, duration:157.6 ms, mean:4371.0 GB/sec, stdev=4.1 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
L1 BW, GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, traffic:26843545600 bytes, duration:3.2 ms, mean:8297.4 GB/sec, stdev=11.6 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
LDS BW, GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, traffic:33554432000 bytes, duration:1.8 ms, mean:18839.2 GB/sec, stdev=44.5 GB/sec
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak FLOPs (FP32), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:274877906944, duration:14.441 ms, mean:19037.6 GFLOPS, stdev=2.7 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak FLOPs (FP64), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:137438953472, duration:7.5 ms, mean:18402.255859.1 GFLOPS, stdev=20.1 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (BF16), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:2147483648000, duration:13.9 ms, mean:154240.3 GFLOPS, stdev=119.3 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F16), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:2147483648000, duration:14.5 ms, mean:148450.1 GFLOPS, stdev=112.6 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F32), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:536870912000, duration:14.4 ms, mean:37335.2 GFLOPS, stdev=43.1 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA FLOPs (F64), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, FLOP:268435456000, duration:7.2 ms, mean:37105.3 GFLOPS, stdev=39.5 GFLOPS
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
Peak MFMA IOPs (I8), GPU ID: 1, workgroupSize:256, workgroups:16384, experiments:100, IOP:2147483648000, duration:14.3 ms, mean:150317.8 GOPS, stdev=203.5 GOPS
```
You will notice two stages in *default* Omniperf profiling. The first stage collects all the counters needed for Omniperf analysis (omitting any filters you have provided). The second stage collects data for the roofline analysis (this stage can be disabled using `--no-roof`)
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In this document, we use the term System on Chip (SoC) to refer to a particular family of accelerators. At the end of profiling, all resulting csv files should be located in a SoC specific target directory, e.g.:
- "mi200" for the AMD Instinct (tm) MI200 family of accelerators
- "mi100" for the AMD Instinct (tm) MI100 family of accelerators
etc. The SoC names are generated as a part of Omniperf, and do not necessarily distinguish between different accelerators in the same family (e.g., an AMD Instinct (tm) MI210 vs an MI250)
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> Note: Additionally, you will notice a few extra files. An SoC parameters file, *sysinfo.csv*, is created to reflect the target device settings. All profiling output is stored in *log.txt*. Roofline specific benchmark results are stored in *roofline.csv*.
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```shell-session
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$ ls workloads/vcopy/mi200/
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total 112
drwxrwxr-x 3 colramos colramos 4096 Apr 11 16:42 .
drwxrwxr-x 3 colramos colramos 4096 Apr 11 16:42 ..
-rw-rw-r-- 1 colramos colramos 40750 Apr 11 16:44 log.txt
drwxrwxr-x 2 colramos colramos 4096 Apr 11 16:42 perfmon
-rw-rw-r-- 1 colramos colramos 25877 Apr 11 16:42 pmc_perf.csv
-rw-rw-r-- 1 colramos colramos 1716 Apr 11 16:44 roofline.csv
-rw-rw-r-- 1 colramos colramos 429 Apr 11 16:42 SQ_IFETCH_LEVEL.csv
-rw-rw-r-- 1 colramos colramos 366 Apr 11 16:42 SQ_INST_LEVEL_LDS.csv
-rw-rw-r-- 1 colramos colramos 391 Apr 11 16:42 SQ_INST_LEVEL_SMEM.csv
-rw-rw-r-- 1 colramos colramos 384 Apr 11 16:42 SQ_INST_LEVEL_VMEM.csv
-rw-rw-r-- 1 colramos colramos 509 Apr 11 16:42 SQ_LEVEL_WAVES.csv
-rw-rw-r-- 1 colramos colramos 498 Apr 11 16:42 sysinfo.csv
-rw-rw-r-- 1 colramos colramos 309 Apr 11 16:42 timestamps.csv
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```
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### Filtering
To reduce profiling time and the counters collected one may use profiling filters. Profiling filters and their functionality depend on the underlying profiler being used. While Omniperf is profiler agnostic, we have provided a detailed description of profiling filters available when using Omniperf with [rocProf](https://rocm.docs.amd.com/projects/rocprofiler/en/latest/rocprof.html) below.
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Filtering Options:
- The `-k` \<kernel> flag allows for kernel filtering. Useage is equivalent with the current rocProf utility ([see details below](#kernel-filtering)).
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- The `-d` \<dispatch> flag allows for dispatch ID filtering. Useage is equivalent with the current rocProf utility ([see details below](#dispatch-filtering)).
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- The `-b` \<ipblocks> allows system profiling on one or more selected hardware components to speed up the profiling process. One can gradually include more hardware components, without overwriting performance data acquired on other hardware components.
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```{note}
Be cautious while combining different profiling filters in the same call. Conflicting filters may result in error.
i.e. filtering dispatch X, but dispatch X does not match your kernel name filter
```
#### Hardware Component Filtering
One can profile specific hardware components to speed up the profiling process. In Omniperf, we use the term IP block to refer 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, hence enabling the incremental profiling and analysis.
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The following example only gathers hardware counters for the Shader Sequencer (SQ) and L2 Cache (TCC) components, skipping all other hardware components:
```shell-session
$ omniperf profile --name vcopy -b SQ TCC -- ./sample/vcopy 1048576 256
Resolving rocprof
ROC Profiler: /usr/bin/rocprof
-------------
Profile only
-------------
omniperf ver: 1.0.8-PR1
Path: /home/colramos/GitHub/omniperf-pub/workloads
Target: mi200
Command: /home/colramos/vcopy 1048576 256
Kernel Selection: None
Dispatch Selection: None
IP Blocks: ['SQ', 'TCC']
fname: pmc_sq_perf2: Added
fname: pmc_td_perf: Skipped
fname: pmc_tcc2_perf: Skipped
fname: pmc_tcp_perf: Skipped
fname: pmc_spi_perf: Skipped
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fname: pmc_sq_perf4: Added
fname: pmc_sqc_perf1: Skipped
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fname: pmc_tcc_perf: Added
fname: pmc_cpf_perf: Skipped
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fname: pmc_sq_perf8: Added
fname: pmc_cpc_perf: Skipped
fname: pmc_sq_perf1: Added
fname: pmc_ta_perf: Skipped
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fname: pmc_sq_perf3: Added
fname: pmc_sq_perf6: Added
Log: /home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/log.txt
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...
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```
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#### Kernel Filtering
Kernel filtering is based on the name of the kernel(s) you would like to isolate. Use a kernel name substring list to isolate desired kernels.
The following example demonstrates profiling isolating the kernel matching substring "vecCopy":
```shell-session
$ omniperf profile --name vcopy -k vecCopy -- ./vcopy 1048576 256
Resolving rocprof
ROC Profiler: /usr/bin/rocprof
-------------
Profile only
-------------
omniperf ver: 1.0.8-PR1
Path: /home/colramos/GitHub/omniperf-pub/workloads
Target: mi200
Command: /home/colramos/vcopy 1048576 256
Kernel Selection: ['vecCopy']
Dispatch Selection: None
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IP Blocks: All
Log: /home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/log.txt
/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt
RPL: on '230411_170300' from '/opt/rocm-5.2.1' in '/home/colramos/GitHub/omniperf-pub'
RPL: profiling '""/home/colramos/vcopy 1048576 256""'
RPL: input file '/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt'
RPL: output dir '/tmp/rpl_data_230411_170300_29696'
RPL: result dir '/tmp/rpl_data_230411_170300_29696/input0_results_230411_170300'
Finished allocating vectors on the CPU
ROCProfiler: input from "/tmp/rpl_data_230411_170300_29696/input0.xml"
gpu_index =
kernel = vecCopy
... ...
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```
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#### Dispatch Filtering
Dispatch filtering is based on the *global* dispatch index of kernels in a run.
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The following example profiles only the 0th dispatched kernel in execution of the application:
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```shell-session
$ omniperf profile --name vcopy -d 0 -- ./vcopy 1048576 256
Resolving rocprof
ROC Profiler: /usr/bin/rocprof
-------------
Profile only
-------------
omniperf ver: 1.0.8-PR1
Path: /home/colramos/GitHub/omniperf-pub/workloads
Target: mi200
Command: /home/colramos/vcopy 1048576 256
Kernel Selection: None
Dispatch Selection: ['0']
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IP Blocks: All
Log: /home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/log.txt
/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt
RPL: on '230411_170356' from '/opt/rocm-5.2.1' in '/home/colramos/GitHub/omniperf-pub'
RPL: profiling '""/home/colramos/vcopy 1048576 256""'
RPL: input file '/home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200/perfmon/SQ_INST_LEVEL_SMEM.txt'
RPL: output dir '/tmp/rpl_data_230411_170356_30314'
RPL: result dir '/tmp/rpl_data_230411_170356_30314/input0_results_230411_170356'
Finished allocating vectors on the CPU
ROCProfiler: input from "/tmp/rpl_data_230411_170356_30314/input0.xml"
gpu_index =
kernel =
range = 0
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...
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```
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### Standalone Roofline
If you are only interested in generating roofline analysis data try using `--roof-only`. This will only collect counters relevant to roofline, as well as generate a standalone .pdf output of your roofline plot.
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Standalone Roofline Options:
- The `--sort` \<desired_sort> allows you to specify whether you would like to overlay top kernel or top dispatch data in your roofline plot.
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- The `-m` \<cache_level> allows you to specify specific level(s) of cache you would like to include in your roofline plot.
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- The `--device` \<gpu_id> allows you to specify a device id to collect performace data from when running our roofline benchmark on your system.
- If you would like to distinguish different kernels in your .pdf roofline plot use `--kernel-names`. This will give each kernel a unique marker identifiable from the plot's key.
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#### Roofline Only
The following example demonstrates profiling roofline data only:
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```shell-session
$ omniperf profile --name vcopy --roof-only -- ./vcopy 1048576 256
Resolving rocprof
ROC Profiler: /usr/bin/rocprof
--------
Roofline only
--------
Checking for roofline.csv in /home/colramos/GitHub/omniperf-pub/workloads/vcopy/mi200
No roofline data found. Generating...
Empirical Roofline Calculation
Copyright © 2022 Advanced Micro Devices, Inc. All rights reserved.
Total detected GPU devices: 4
GPU Device 0: Profiling...
99% [||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ]
... ...
Checking for roofline.csv in /home/colramos/GitHub/omniperf-pub/workloads/mix/mi200
Checking for sysinfo.csv in /home/colramos/GitHub/omniperf-pub/workloads/mix/mi200
Checking for pmc_perf.csv in /home/colramos/GitHub/omniperf-pub/workloads/mix/mi200
Empirical Roofline PDFs saved!
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```
An inspection of our workload output folder shows .pdf plots were generated successfully
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```shell-session
$ ls workloads/vcopy/mi200/
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total 176
drwxrwxr-x 3 colramos colramos 4096 Apr 11 17:18 .
drwxrwxr-x 3 colramos colramos 4096 Apr 11 17:15 ..
-rw-rw-r-- 1 colramos colramos 13271 Apr 11 17:18 empirRoof_gpu-ALL_fp32.pdf
-rw-rw-r-- 1 colramos colramos 13175 Apr 11 17:18 empirRoof_gpu-ALL_int8_fp16.pdf
-rw-rw-r-- 1 colramos colramos 26560 Apr 11 17:16 log.txt
drwxrwxr-x 2 colramos colramos 4096 Apr 11 17:16 perfmon
-rw-rw-r-- 1 colramos colramos 54031 Apr 11 17:16 pmc_perf.csv
-rw-rw-r-- 1 colramos colramos 1714 Apr 11 17:16 roofline.csv
-rw-rw-r-- 1 colramos colramos 457 Apr 11 17:16 sysinfo.csv
-rw-rw-r-- 1 colramos colramos 37521 Apr 11 17:16 timestamps.csv
```
A sample *empirRoof_gpu-ALL_fp32.pdf* looks something like this:
![Sample Standalone Roof Plot](images/sample-roof-plot.png)