GitLab

**Description**
Updated docker for 12.8
Use cutlass latest relase 3.8 with ARCH 100(blackwell) support
add latest nccl-test release with ARCH 100(blackwell) 
Updated msccl to support build for sm_100
No breaking changes, so backward compatible tested with  cuda 12.4

---------
Co-authored-by: Hongtao Zhang <garyworkzht@gmail.com>

Co-authored-by: Yifan Xiong <yifan.xiong@microsoft.com>
Co-authored-by: Hongtao Zhang <garyworkzht@gmail.com>

Root Cause:

1. '_get_all_test_cases()' was called in '_parser' while '_parser' was
defined in the base class.
2.  in '_get_all_test_cases()', cmd path was not included.

Fix:

1. Remove '_get_all_test_cases()' from '_parser'.
2. Construct path for cmd.

---------
Co-authored-by: hongtaozhang <hongtaozhang@microsoft.com>

**Description**

1. Fixed the bug that nvbandwidth benchmark need to handle 'N/A' values
in nvbandwidth cmd output.
2. Replaced the input format of test cases with a list.
3. Add nvbandwidth configuration example in default config files.

---------
Co-authored-by: hongtaozhang <hongtaozhang@microsoft.com>
Co-authored-by: Yifan Xiong <yifan.xiong@microsoft.com>

**Description**
Today I was running a benchmark on my machine. And encountered a fancy
issue with tensorrt-inference.
I got code 33, which according to the source code is:
```
MICROBENCHMARK_RESULT_PARSING_FAILURE = 33
```
I dived deep into the code and found out the following problem. The
parser stumbled upon getting to the following line:
```
[11/28/2024-17:03:11] [I] Latency: min = 7.2793 ms, max = 10.1606 ms, mean = 7.41642 ms, median = 7.39551 ms, percentile(99%) = 8 ms
```
I ran it separately on the code and found out that the regular
expression was not suitable for the cases like this, when you encounter
an INT as a result in milliseconds.
That's why this pull request is created.
I came up with the closest possible regular expression to fix this issue
and not to introduce any other bug.

**Major Revision**
- 0.11.0

**Description**
Introduce architecture support for version 10.0 in gemm-flops.

Added llama benchmark - training and inference in accordance with the
existing pytorch models implementation like gpt2, lstm etc.

- added llama fp8 unit test for better code coverage, to reduce memory
required
- updated transformers version >= 4.28.0 for LLamaConfig
- set tokenizers version <= 0.20.3 to avoid 0.20.4 version
[issues](https://github.com/huggingface/tokenizers/issues/1691

) with
py3.8
- added llama2 to tensorrt
- llama2 tests not added to test_tensorrt_inference_performance.py due
to large memory requirement for worker gpu. tests validated separately
on gh200

---------
Co-authored-by: dpatlolla <dpatlolla@microsoft.com>

Fix ordering of args in err messages.

**Description**

Add nvbandwidth benchmark.

---------
Co-authored-by: hongtaozhang <hongtaozhang@microsoft.com>

**Description**
Add micro benchmark to measure general CPU bandwidth and latency without 'mlc'.

Test output:
```
{
"cpu-memory-bw-latency/return_code": 0,
"cpu-memory-bw-latency/mem_bandwidth_matrix_numa_0_1_bw": 5388.75021,
"cpu-memory-bw-latency/mem_bandwidth_matrix_numa_0_1_lat": 0.185571786,
"cpu-memory-bw-latency/mem_bandwidth_matrix_numa_1_0_bw": 4634.82028,
"cpu-memory-bw-latency/mem_bandwidth_matrix_numa_1_0_lat": 0.215758096,
}
```

---------
Co-authored-by: hongtaozhang <hongtaozhang@microsoft.com>

Add support for arm64 build:

- Updated dockerfile for arm64 build
- extend cpu stream compilation for neoverse 
- handle onnxruntime-gpu installation
- third party builds filtering based on arch
- disable cuda decode perf build for non x86

The current GPU Copy BW Performance fails on Nvidia Grace systems. This
is due to the memory only numa node and thus the numa_run_on_node fails
for such nodes and halts completely.

This fix checks for the presence of assigned CPU cores for the numa
node, on checking if it has no cpu cores assigned, it skips that
specific node during the args creation and continues.

**Description**
Add support GPU ARCH 8.9 for NVIDIA L4/L40/L40s GPUs in gemm-flops.

**Description**
Adds hipblasLt tuning to dist-inference cpp implementation.

**Description**

Cherry-pick bug fixes from v0.10.0 to main.

**Major Revisions**

* Benchmarks: Microbenchmark - Support different hipblasLt data types in dist_inference #590
* Benchmarks: Microbenchmark - Support in-place for NCCL/RCCL benchmark #591
* Bug Fix - Fix NUMA Domains Swap Issue in NDv4 Topology File #592
* Benchmarks: Microbenchmark - Add data type option for NCCL and RCCL tests #595
* Benchmarks: Bug Fix - Make metrics of dist-inference-cpp aligned with PyTorch version #596
* CI/CD - Add ndv5 topo file #597
* Benchmarks: Microbenchmark - Improve AMD GPU P2P performance with fine-grained GPU memory #593
* Benchmarks: Build Pipeline - fix nccl and nccl test version to 2.18.3 to resolve hang issue in cuda12.2 docker #599
* Dockerfile - Bug fix for rocm docker build and deploy #598
* Benchmarks: Microbenchmark - Adapt to hipblasLt data type changes #603
* Benchmarks: Micro benchmarks - Update hipblaslt metric unit to tflops #604
* Monitor - Upgrade pyrsmi to amdsmi python library. #601
* Benchmarks: Micro benchmarks - add fp8 and initialization for hipblaslt benchmark #605
* Dockerfile - Add rocm6.0 dockerfile #602
* Bug Fix - Bug fix for latest megatron-lm benchmark #600
* Docs - Upgrade version and release note #606
Co-authored-by: Ziyue Yang <ziyyang@microsoft.com>
Co-authored-by: Yang Wang <yangwang1@microsoft.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>
Co-authored-by: guoshzhao <guzhao@microsoft.com>

**Description**
`add_compile_options` will not work for ROCm build, change it to setting
`CMAKE_CXX_FLAGS`.

**Description**
Add distributed inference benchmark cpp implementation.

**Description**
upgrade to rocm5.7 dockerfile.

---------
Co-authored-by: yukirora <yuting.jiang@microsoft.com>

Benchmarks: Micro benchmark - Add one-to-all, all-to-one, all-to-all support to gpu_copy_bw_performance (#588)

**Description**
Add one-to-all, all-to-one, all-to-all support to
gpu_copy_bw_performance, and fix performance bug in gpu_copy

**Description**
Revise NCCL/RCCL benchmarks to graph mode add latency metrics.

**Description**
Benchmarks: micro benchmark - Support cpu-gpu and gpu-cpu in
ib-validation

**Major Revision**
- Support cpu-gpu and gpu-cpu in ib-validation


**Minor Revision**
- support multi msg size, multi direction, multi ib commands in
ib-validation

Upgrade Docker image to CUDA 12.2 for H100:
* upgrade base image to 23.10
* fix onnxruntime version in python3.10
* fix compilation errors

**Description**
add initialization options for rocm gemm flops.

**Description**
hipblaslt function benchmark and rebase cublaslt function benchmark.

**Description**
add int8 support for cublaslt function.

**Description**
remove cp ptx file in gpu burn test since the command is run inside
self.args.bin_dir dir.


https://github.com/microsoft/superbenchmark/blob/d246bab430adeb461072918a551b2e2b68c9bce5/superbench/benchmarks/micro_benchmarks/micro_base.py#L183

**Description**
source code for evaluating NVDEC decoding performance.

---------
Co-authored-by: yukirora <yuting.jiang@microsoft.com>

**Description**
add source code for DirectXRenderPerf.

---------
Co-authored-by: yukirora <yuting.jiang@microsoft.com>

**Description**
Cherry-pick bug fixes from v0.9.0 to main.

**Major Revision**
- CI/CD: pipeline - clean more disk space to fix rocm building image
pipeline(#555 )
- Benchmarks: bug fix - use absolute path for input file in
DirectXEncodingLatency(#554)
- CI/CD - add push win docker image on release branch in pipeline (#552)
- Docs - Upgrade version and release note(#557)

**Description**
add python code for DirectXGPUEncodingLatency.

**Description**
add python code for DirectXGPUCopy.

**Description**
add python code for DirecXGPUMemBw.

**Description**
add python code for DirectX core flops and init DirectX test pipeline.

**Major Revision**
- add python code for DirectX core flops 
- init DirectX test pipeline


**Minor Revision**
- add test for DirectX core flops

**Description**
add auto selecting algorithm support for cudnn functions.

**Major Revision**
- add auto selecting algorithm support for cudnn functions in source
code
- add 'auto_algo' option in benchmark
- add related test

* Update result parsing for newer tensorrt versions
* Update arguments when load torchvision models

**Description**
Add source code of DirectxGPUCopy microbenchmark.

**Description**
Add source code of DirectxGPUMemBw microbenchmark.

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Co-authored-by: v-junlinlv <v-junlinlv@microsoft.com>

**Description**
Add source code of DirectXGPUCoreFLOPs microbenchmark.

---------
Co-authored-by: v-junlinlv <v-junlinlv@microsoft.com>

**Description**
This commit revises distributed inference benchmark to give a unified
step time result by taking maximum step times of different GPUs.

**Description**

Cherry-pick bug fixes from v0.8.0 to main.

**Major Revisions**

* Monitor - Fix the cgroup version checking logic (#502)
* Benchmark - Fix matrix size overflow issue in cuBLASLt GEMM (#503)
* Fix wrong torch usage in communication wrapper for Distributed
Inference Benchmark (#505)
* Analyzer: Fix bug in python3.8 due to pandas api change (#504)
* Bug - Fix bug to get metric from cmd when error happens (#506)
* Monitor - Collect realtime GPU power when benchmarking (#507)
* Add num_workers argument in model benchmark (#511)
* Remove unreachable condition when write host list (#512)
* Update cuda11.8 image to cuda12.1 based on nvcr23.03 (#513)
* Doc - Fix wrong unit of cpu-memory-bw-latency in doc (#515)
* Docs - Upgrade version and release note (#508)
Co-authored-by: guoshzhao <guzhao@microsoft.com>
Co-authored-by: Ziyue Yang <ziyyang@microsoft.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>