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**Description**
Integrate FAMBench into superbench based on docker implementation:
https://github.com/facebookresearch/FAMBench

The script to run all benchmarks is:
https://github.com/facebookresearch/FAMBench/blob/main/benchmarks/run_all.sh

**Description**
Integrate output all nodes diagnosis results.

**Description**
Output results of all nodes in data diagnosis.

**Description**
Integrage result summary and update output format of data diagnosis.

**Major Revision**
- integrage result summary 
- add md and html format for data diagnosis

**Description**
Use config `log_raw_data` to control whether log the raw data into file or not. The default value is `no`. We can set it as `yes` for some particular benchmarks to save the raw data into file, such as NCCL/RCCL test.

**Description**
Add result summary in excel,md,html format.

**Major Revision**
- Add ResultSummary class to support result summary in excel,md,html format.
- Abstract RuleBase class for common-used functions in DataDiagnosis and ResultSummary.

**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

**Description**
Add md and html output format for DataDiagnosis.

**Major Revision**
- add md and html support in file_handler
- add interface in DataDiagnosis for md and HTML output

**Minor Revision**
- move excel and json output interface into DataDiagnosis

**Description**
Abstract RuleBase from DataDiagnosis.

**Description**
Add multi-rules feature for data diagnosis to support multiple rules' combined check.

**Major Revision**
- revise rule design to support multiple rules combination check
- update related codes and tests

**Description**
This commit remove NUMA binding for device-to-device tests because NUMA doesn't affect performance, and revise benchmark metrics accordingly.

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

**Description**
This commit does the following to optimize result variance in gpu_copy benchmark:
1) Add warmup phase for gpu_copy benchmark to avoid timing instability caused by first-time CUDA kernel launch overhead;
2) Use CUDA events for timing instead of CPU timestamps;
3) Make data checking an option that is not preferred to be enabled in performance test;
4) Enlarge message size in performance benchmark.

Support T4 and A10 in GEMM benchmark.

Support customized env for all modes in configuration.

**Description**
Please write a brief description and link the related issue if have.

**Major Revision**
- Sync (do allreduce max) the E2E training results among all workers.
- Avoid using ':0' in metric name if there has only one rank having output.

**Description**
Add timeout feature for each benchmark.

**Major Revision**
- Add `timeout` config for each benchmark. In current config files, only set the timeout for kernel-launch as example. Other benchmarks can be set in the future.
- Set the timeout config for `ansible_runner.run()`. Runner will get the return code 254:
   [ansible.py:80][WARNING] Run failed, return code 254.
- Using `timeout` command to terminate the client process.

__Description__

Update benchmark naming to support annotations.

__Major Revisions__
- Update name for `create_benchmark_context` in executor.
- Backward compatibility for model benchmarks using "_models" suffix.
- Update documents.

**Description**
This commit adds bidirectional tests in gpu_copy benchmark for both device-host transfer and device-device transfer, and revises related tests.

**Description**
Add 50th, 90th, 95th, 99th, 99.9th latency metrics for ORT and pytorch inference benchmarks.

__Description__

Add command `sb benchmark list` and `sb benchmark list-parameters` to support listing all optional parameters for benchmarks.

<details>
<summary>Examples</summary>
<pre>
$ sb benchmark list -n [a-z]+-bw -o table
Result
--------
mem-bw
nccl-bw
rccl-bw
</pre>
<pre>
$ sb benchmark list-parameters -n mem-bw
=== mem-bw ===
optional arguments:
  --bin_dir str         Specify the directory of the benchmark binary.
  --duration int        The elapsed time of benchmark in seconds.
  --mem_type str [str ...]
                        Memory types to benchmark. E.g. htod dtoh dtod.
  --memory str          Memory argument for bandwidthtest. E.g. pinned unpinned.
  --run_count int       The run count of benchmark.
  --shmoo_mode          Enable shmoo mode for bandwidthtest.
default values:
{'bin_dir': None,
 'duration': 0,
 'mem_type': ['htod', 'dtoh'],
 'memory': 'pinned',
 'run_count': 1}
</pre>
</details>

__Major Revisions__
* Add `sb benchmark list` to list benchmarks matching given name.
* Add `sb benchmark list-parameters` to list parameters for benchmarks which match given name.

__Minor Revisions__
* Sort format help text for argparse.

__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>

Add transformers for TensorRT inference.

**Description**
Add benchmark metrics for cpu-memory-bw-latency.

**Description**
Benchmarks: Fix Comment - Correct benchmark name in test_gpu_copy_bw_performance.py.

**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**
Add basic analysis features.

**Major Revision**
- Add statistics, correlations of the raw data
- Add numeric outlier detection(inter_quartile_range)
- Add boxplot for selected metric

**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.

**Description**
Set the `reduce_op` type for metirc `return_code` as `None`.

**Description**
Add cli to integrate data diagnosis module.

**Description**
Unify metric names of benchmarks.

**Description**
Add data diagnosis module.

**Major Revision**
- Add DataDiagnosis class to support rule-based data diagnosis for result summary jsonl file of multi nodes
- Add RuleOp class to define rule operators

**Description**
Add return_code metric into result and revise unit tests.

**Description**
If `ignore_invalid` is True, and 'required' arguments are not set when register the benchmark, the arguments should be provided by user in config and skip the arguments checking.

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

**Description**
Add the initial version of Monitor.

**Major Revision**
- Add `Monitor` class to launch background process for monitoring.
- Add `MonitorRecord` class to save the data one time capturing.

**Description**
Rename `nvidia_helper` utility as `device_manager` module and support more functions:
```
device_manager.get_device_count()
device_manager.get_device_utilization(idx)
device_manager.get_device_temperature(idx)
device_manager.get_device_power_limit(idx)
device_manager.get_device_memory(idx)
device_manager.get_device_row_remapped_info(idx)
device_manager.get_device_ecc_error(idx)
```

__Description__

Add TensorRT inference benchmark for torchvision models.

__Major Revision__
- Measure TensorRT inference performance.

**Description**
Add ib traffic validation distributed benchmark.

**Major Revision**
- Add ib traffic validation distributed benchmark, example and test