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**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.

Update version to include revision hash and date in "{last tag}+g{git
hash}.d{date}" format, here're the examples:
* exact tag: 0.6.0
* commit after tag: 0.6.0+gcbb1b34
* commit after tag with local changes: 0.6.0+gcbb1b34.d20221028

Benchmarks - Add support to allow list of custom config string in cudnn-functions and cublas-functions (#414)

**Description**
Add support to allow list of custom config string in cudnn-functions and cublas-functions.

**Description**

Cherry-pick bug fixes from v0.6.0 to main.

**Major Revisions**

* Enable latency test in ib traffic validation distributed benchmark (#396)
* Enhance parameter parsing to allow spaces in value (#397)
* Update apt packages in dockerfile (#398)
* Upgrade colorlog for NO_COLOR support (#404)
* Analyzer - Update error handling to support exit code of sb result diagnosis (#403)
* Analyzer - Make baseline file optional in data diagnosis and fix bugs (#399)
* Enhance timeout cleanup to avoid possible hanging (#405)
* Auto generate ibstat file by pssh (#402)
* Analyzer - Format int type and unify empty value to N/A in diagnosis output file (#406)
* Docs - Upgrade version and release note (#407)
* Docs - Fix issues in document (#408)
Co-authored-by: Yang Wang <yangwang1@microsoft.com>
Co-authored-by: Yuting Jiang <yutingjiang@microsoft.com>

**Description**
Add support to store values of metrics in data diagnosis.

Take the following rules as example: 
```
    nccl_store_rule:
      categories: NCCL_DIS
      store: True
      metrics:
        - nccl-bw:allreduce-run0/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run1/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run2/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run3/allreduce_1073741824_busbw
        - nccl-bw:allreduce-run4/allreduce_1073741824_busbw
    nccl_rule:
      function: multi_rules
      criteria: 'lambda label:True if min(label["nccl_store_rule"].values())/max(label["nccl_store_rule"].values())<0.95 else False'
      categories: NCCL_DIS
```
**nccl_store_rule** will store the values of the metrics in dict and save them into `label["nccl_store_rule"]` , and then **rccl_rule** can use the values of metrics through `label["nccl_store_rule"].values()` in criteria

**Description**
Add support for both jsonl and json format in data diagnosis.

**Major Revision**
- Add support for both jsonl and json format in data diagnosis


**Minor Revision**
- change related doc
- add jsonl support in cli