add fused_deep_moe test for dispatch_ffn_combine

[zuje123]

Add precision and performance tests for the dispatch_ffn_combine kernel.

Config:
num_ranks=16, num_tokens=256, hidden=7168, moe_intermediate_size=4096, num_topk=8, num_experts=256
Performance:
[Rank 0] baseline_time= 1397.98 us, fused2_moe_time= 1018.74 us
[Rank 14] baseline_time= 1396.71 us, fused2_moe_time= 1018.92 us
[Rank 2] baseline_time= 1397.98 us, fused2_moe_time= 1018.96 us
[Rank 1] baseline_time= 1397.91 us, fused2_moe_time= 1018.72 us
[Rank 12] baseline_time= 1397.32 us, fused2_moe_time= 1018.70 us
[Rank 4] baseline_time= 1397.52 us, fused2_moe_time= 1018.96 us
[Rank 9] baseline_time= 1396.74 us, fused2_moe_time= 1018.61 us
[Rank 10] baseline_time= 1396.40 us, fused2_moe_time= 1018.79 us
[Rank 5] baseline_time= 1396.78 us, fused2_moe_time= 1018.89 us
[Rank 7] baseline_time= 1397.38 us, fused2_moe_time= 1018.79 us
[Rank 3] baseline_time= 1397.37 us, fused2_moe_time= 1018.70 us
[Rank 13] baseline_time= 1397.14 us, fused2_moe_time= 1018.64 us
[Rank 11] baseline_time= 1397.46 us, fused2_moe_time= 1019.02 us
[Rank 6] baseline_time= 1396.93 us, fused2_moe_time= 1018.82 us

[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a dedicated test for the dispatch_ffn_combine kernel, which is a component of the fused_deep_moe operation. The primary goal is to ensure the kernel's numerical precision and to benchmark its performance against a step-by-step baseline implementation. The changes include new utility functions for test setup, a detailed comparison logic, and performance measurements, ultimately showing a substantial speedup for the fused operation.

Highlights

• New Test for dispatch_ffn_combine: A new test suite has been added to validate the dispatch_ffn_combine kernel, focusing on both precision and performance.
• Precision and Performance Benchmarking: The new test includes a comprehensive comparison between a baseline implementation and the fused_deep_moe kernel in dispatch_ffn_combine mode, demonstrating significant performance improvements (e.g., from ~1400 us to ~1000 us).
• Weight Initialization and Utility Functions: Several helper functions (init_base_weights, init_baseline_weights, init_fused2_weights_int8, scale_from_float_to_int64, make_uniform_topk_idx, from_inclusive_prefix_sum) were introduced to streamline weight setup and data manipulation for the tests.
• Configurable Active Ranks and Debugging: New command-line arguments --active-ranks and --debug were added to allow for more flexible testing configurations and detailed logging.

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Ignored Files

• Ignored by pattern: .github/workflows/** (1)
  • .github/workflows/pr-test-npu.yml

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[gemini-code-assist]

Code Review

This pull request introduces a comprehensive test for the dispatch_ffn_combine kernel, including both precision and performance evaluations against a baseline. It also includes refactoring of the existing test_fused_deep_moe.py to align with the new test structure and apply some correctness fixes. The changes add valuable test coverage. My review includes suggestions to improve code quality and maintainability by addressing a local import, the use of magic numbers, and a redundant process group creation.