GitLab

Update `omegaconf` version to
[2.3.0](https://pypi.org/project/omegaconf/2.3.0/) as omegaconf 2.0.6
has a non-standard dependency specifier PyYAML>=5.1.*. pip 24.1 will
enforce this behaviour change.
Discussion can be found at https://github.com/pypa/pip/issues/12063.

**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 distributed inference benchmark cpp implementation.

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**
Megatron-LM/Megatron-Deepspeed GPT pretrain benchmark

**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

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

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

**Description**
Generate baseline given results from multiple nodes. 

**Major Revision**
- Add sub command `sb result generate-baseline`
- Add UT and docs

---------
Co-authored-by: 454314380 <454314380@qq.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**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

This PR has following changes
- torch.distributed.launch changed to torchrun. torch.distributed.launch
is deprecated in latest Pytorch and is recommended to move to torchrun -
https://pytorch.org/docs/stable/elastic/run.html


- Changes to AMD GPU detection logic. The AMD GPU detection logic throws
warning when containers have only renderD in /dev/dri, this change would
resolve those warnings

---------
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**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**
Support DirectX test pipeline.

**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**
Model benchmarks can stop due to `num_steps` or `duration` config which
will take effect when the value is set greater than 0.
If both are set greater than 0, the earliest condition reached will
work.

**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>

**Description**
This PR adds a micro-benchmark of distributed model inference workloads.

**Major Revision**
- Add a new micro-benchmark dist-inference.
- Add corresponding example and unit tests.
- Update configuration files to include this new micro-benchmark.
- Update micro-benchmark README.

---------
Co-authored-by: Peng Cheng <chengpeng5555@outlook.com>

**Description**
Since ubuntu 22.04 will use cgroup V2 and the file structure changed.
Modify the monitor to adapt to cgroup v1 and v2.

Support batch and shape range with multiplication factors in cublaslt
gemm benchmark.

**Description**

- Adding HPL benchmark

---------
Co-authored-by: Ubuntu <azureuser@sbtestvm.jzlku1oskncengjiado35wf1hd.ax.internal.cloudapp.net>
Co-authored-by: Peng Cheng <chengpeng5555@outlook.com>

**Description**

- Added stream benchmark
- Added stream unit test
- Added stream example
- Modified docker files to build stream

---------
Co-authored-by: Ubuntu <azureuser@sbtestvm.jzlku1oskncengjiado35wf1hd.ax.internal.cloudapp.net>
Co-authored-by: Peng Cheng <chengpeng5555@outlook.com>
Co-authored-by: Yifan Xiong <xiongyf@yandex.com>

**Description**

Cherry-pick bug fixes from v0.7.0 to main.

**Major Revisions**

* Benchmarks - Fix missing include in FP8 benchmark (#460)
* Fix bug in TE BERT model (#461)
* Doc - Update benchmark doc (#465)
* Bug: Fix bug for incorrect datatype judgement in cublas-function
source code (#464)
* Support `sb deploy` without pulling image (#466)
* Docs - Upgrade version and release note (#467)
Co-authored-by: Russell J. Hewett <russell.j.hewett@gmail.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

Support traffic patterns under the different devices in NCCL/RCCL test
* change the metrics format if specified the pattern

**Major Revision**

- Add an option for pattern to generate mpi_pattern.txt file if
specified the path.
- In mpi pattern, serial_index and parallel_index will add in each
benchmark as environment variables.

**Minor Revision**
- Fix typo

Support FP8 in PyTorch BERT models:

* add fp8 hybrid/e4m3/e5m2 in precision arguments
* build BERT encoders with `te.TransformerLayer` to repalce
`transformers.BertModel`
* wrap forward steps with fp8 autocast

**Description**
Support the following patterns  in `mpi` mode:
* `k-batch`
* `topo-aware`

Integrate cublaslt-gemm micro-benchmark #451.

**Description**
 Add correctness check in cublas-function benchmark.

**Major Revision**
- add python code of correctness check in cublas-function benchmark and test

**Description**
Add stdout logging util module and enable real-time logging flushing in executor

**Major Revision**
- Add stdout logging util module to redirect stdout into file log
- enable stdout logging in executor to write benchmark output into both stdout and file `sb-bench.log`
- enable real-time log flushing in run_command of microbenchmarks through config `log_flushing`

**Minor Revision**
- add log_n_step args to enable regular step time log in model benchmarks 
- udpate related docs

* Extract pair-wise pattern from ib_validation

**Description**
Add wait time option to resolve mem-bw unstable issue.

* add mpi-parallels mode

* update according to comments

* fix and update doc

* update

* merge into 'mpi' mode

* udpate according to comments

* fix testcases

* fix ansible

* regard pattern as field

* udpate

* fix flake8 version

* add flake8 range

* remove map-by from host config

* udpate comments

Add non-zero return code for `sb deploy` and `sb run` command when
there're Ansible failures in control plane.
Return code is set to count of failure.

For failures caused by benchmarks, return code is still set per benchmark
in results json file.