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**Description**
This PR adds NCU (NVIDIA Nsight Compute) profiling support to the
cublaslt-gemm micro benchmark, enabling detailed kernel analysis
including DRAM throughput, compute throughput, and launch arguments.

**Major Revision**
- Add --enable_ncu_profiling and --profiling_metrics for ncu profiling
- Modifies command execution to use NCU when profiling is enabled
- Updates result parsing to handle both standard and NCU profiled output
formats

**Description**
Add FP4 precision support for cublaslt_gemm benchmark.

**Major Revision**
- Add new type `fp4e2m1` and `__nv_fp4_e2m1`.
- For FP4 matmul, precision of MatrixC (add) should be FP16, precision
of MatricD (output) should be FP4, otherwise, it will not work.
- Add macro `CUDA_VERSION` to resolve the compatibility issue of
different CUDA versions.

---------
Co-authored-by: Ubuntu <aiperf@aiperf000000.hp5z1gqeinfufbj2u3jcty5fme.cdmx.internal.cloudapp.net>
Co-authored-by: AVA <39534996+avazr@users.noreply.github.com>
Co-authored-by: Guoshuai Zhao <microsoft@microsoft.com>

**Description**
Enable autotuning as an opt-in mode when benchmarking cublasLt via
`cublaslt_gemm`

The implementation is based on
https://github.com/NVIDIA/CUDALibrarySamples/blob/master/cuBLASLt/LtSgemmSimpleAutoTuning/sample_cublasLt_LtSgemmSimpleAutoTuning.cu

The behavior of original benchmark command remains unchanged, e.g.:
- `cublaslt_gemm -m 2048 -n 12288 -k 1536 -w10000 -i 1000 -t fp8e4m3`

The new opt-in options are `-a` (for autotune) and `-I` (for autotune
iterations, default is 50, same as the default for `-i`) and `-W` (for
autotune warmups, default=20, same as the default for `-w`), e.g.:
- `cublaslt_gemm -m 2048 -n 12288 -k 1536 -w 10000 -i 1000 -t fp8e4m3
-a`
- `cublaslt_gemm -m 2048 -n 12288 -k 1536 -w 10000 -i 1000 -t fp8e4m3 -a
-I 10 -W 10`

**Note:** This PR also changes the default `gemm_compute_type` for BF16
and FP16 to `CUBLAS_COMPUTE_32F`.

**Further observations:** 
1. The support matrix of the `cublaslt_gemm` could be furt...

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

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

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

Support FP64/TF32/FP16/BF16 in cublaslt (batch) GEMM.

Integrate cublaslt-gemm micro-benchmark #451.

**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.

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.

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

**Description**
Unify metric names of benchmarks.

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

**Description**
Rename `kernel_launch_overhead_event` to `event_overhead`, `kernel_launch_overhead_wall` to `wall_overhead`.

* add kernel launch overhead benchmark.