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**Description**
Modifications adding GPU-Burn to SuperBench.
- added third party submodule
- modified Makefile to make gpu-burn binary
- added/modified microbenchmarks to add gpu-burn python scripts
- modified default and azure_ndv4 configs to add gpu-burn

This commit adds GDR-only nccl-tests for Nvidia machines. Also bump NCCL to v2.10.3-1 to achieve peak performance in this test.

This commit makes data checking in gpu_copy optional, because it will take too long time if message size is large.

**Description**
Disable disk-benchmark in ndmv4.yaml and change batch size to 1 in default.yaml

__Description__

Cherry-pick  bug fixes from v0.4.0 to main.

__Major Revisions__

* Bug - Fix issues for Ansible and benchmarks (#267)
* Tests - Refine test cases for microbenchmark (#268)
* Bug - Build openmpi with ucx support in rocm dockerfiles (#269)
* Benchmarks: Fix Bug - Fix fio build issue (#272)
* Docs - Unify metric and add doc for cublas and cudnn functions (#271)
* Monitor: Revision - Add 'monitor/' prefix to monitor metrics in result summary (#274)
* Bug - Fix bug of detecting if gpu_index is none (#275)
* Bug - Fix bugs in data diagnosis (#273)
* Bug - Fix issue that the root mpi rank may not be the first in the hostfile (#270)
* Benchmarks: Configuration - Update inference and network benchmarks in configs (#276)
* Docs - Upgrade version and release note (#277)
Co-authored-by: Yuting Jiang <v-yutjiang@microsoft.com>

**Description**
Add mlc memory bandwidth and latency micro benchmark to Superbench.

**Major Revision**
- Add mlc benchmark with test and example files

**Description**
Add ONNXRuntime inference benchmark based on ORT python API.

**Major Revision**
- Add `ORTInferenceBenchmark` class to export pytorch model to onnx model and do inference
- Add tests and example for `ort-inference` benchmark
- Update the introduction docs.

**Description**
Integrate monitor into Superbench.

**Major Revision**
- Initialize, start and stop monitor in SB executor.
- Parse the monitor data in SB runner and merge into benchmark results.
- Specify ReduceType for monitor metrics, such as MAX, MIN and LAST.
- Add monitor configs into config file.

Fix issues for distributed runs:
* fix config for memory bandwidth benchmarks
* add throttling for high concurrency docker pull
* update rsync path and exclude directories
* handle exceptions when creating summary
* tune for logging

**Description**
Replace `-c` argument with `-N` for `numactl` since the old `-c`/`--cpubind` argument is deprecated.

**Description**
This commit does the following:
1) Adds CPU-initiated copy benchmark;
2) Adds dtod benchmark;
3) Support scanning NUMA nodes and GPUs inside the benchmark program;
4) Change the name of gpu-sm-copy to gpu-copy.

**Description**

Cherry-pick  bug fixes from v0.3.0 to main.

**Major Revisions**
* Docs - Upgrade version and release note (#209)
* Benchmarks: Build Pipeline - Update rccl-test git submodule to dc1ad48 (#210)
* Benchmarks: Update - Update benchmarks in configuration file (#208)
* CI/CD - Update GitHub Action VM (#211)
* Benchmarks: Fix Bug - Fix wrong parameters for gpu-sm-copy-bw in configuration examples (#203)
* CI/CD - Fix bug in build image for push event (#205)
* Benchmark: Fix Bug - fix error message of communication-computation-overlap (#204)
* Tool: Fix bug - Fix function naming issue in system info  (#200)
* CI/CD - Push images in GitHub Action (#202)
* Bug - Fix torch.distributed command for single node (#201)
* CLI - Integrate system info for node (#199)
* Benchmarks: Code Revision - Revise CMake files for microbenchmarks. (#196)
* CI/CD - Add ROCm image build in GitHub Actions (#194)
* Bug: Fix bug - fix bug of hipBusBandwidth build (#193)
* Benchmarks: Build Pipeline - Restore rocblas build logic (#197)
* Bug: Fix Bug - Add barrier before 'destroy_process_group' in model benchmarks (#198)
* Bug - Revise 'docker run' in sb deploy (#195)
* Bug - Fix Bug : fix bug of error param operations to operation in rccl-bw of hpe config (#190)
Co-authored-by: Yuting Jiang <v-yujiang@microsoft.com>
Co-authored-by: Guoshuai Zhao <guzhao@microsoft.com>
Co-authored-by: Ziyue Yang <ziyyang@microsoft.com>

Benchmarks: Code Revision - Revise metric name generation and default config for disk performance benchmark (#175)

**Description**
This commit revises disk performance benchmark, including:
1) Add missing benchmark name in default config;
2) Avoid using reserved character ':' in metric name.

**Description**
This commit adds gpu_sm_copy benchmark and related tests.

**Description**
Add NCCL performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for NCCL

**Description**
Add RDMA Loopback performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for RDMA Loopback

**Description**
Add disk performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for disk performance.

**Minor Revision**
- Fix bugs in executor unit test related to default enabled tests.

Add microbenchmark, example, test, config for cuda memory performance and Add cuda-samples(tag with cuda version) as git submodule and update related makefile

Update README and version for v0.2 release.

* Add `sb deploy` command content.
* Fix inline if-expression syntax in playbook.
* Fix quote escape issue in bash command.
* Add custom env in config.
* Update default config for multi GPU benchmarks.
* Update MANIFEST.in to include jinja2 template.
* Require jinja2 minimum version.
* Fix occasional duplicate output in Ansible runner.
* Fix mixed color from Ansible and Python colorlog.
* Update according to comments.
* Change superbench.env from list to dict in config file.

Fix bugs and refine log in single GPU benchmarks:

* Fix none framework issue
* Fix empty parameter bug
* Remove missed mobilenet_v3 models
* Change benchmark registration log to debug level
* Add pid in logging
* Add missing benchmarks in default config
* Fix deprecated logging warn

* Support local mode in runner.

* Support `torch.distributed` mode in runner.
* Support given `proc_num` and `node_num` in `torch.distributed` mode.

* fix missing package in dockerfile
* update benchmark list and parameters
* catch runtime errors
* refine logging info

Add superbench executor class

* add executor class
* update default config to exec benchmarks
* add micro benchmarks and model benchmarks

- Add CLI commands
  * sb version
  * sb deploy
  * sb exec
  * sb run
- Add interface with executor and runner
- Add cli test cases