ROCm/composable_kernel
Oct 2025 – Oct 2025
1 Month active
Languages Used
C++
Technical Skills
C++CUDA/HIPGPU ProgrammingHigh-Performance ComputingTemplate Metaprogramming
Manish Kumar
PROFILE
Manish Kumar
In October 2025, Manish Kumar enhanced the ROCm/composable_kernel repository by developing support for grouped GEMM preshuffle and tileloop workflows. He implemented the tile_grouped_gemm_preshuffle feature, introducing a grouped_gemm_tileloop and enabling persistent preshuffle mode to improve the efficiency and scalability of grouped GEMM computations. Using C++, CUDA/HIP, and advanced template metaprogramming, Manish updated tests and utility headers to ensure the new workflow integrated smoothly and maintained CI stability. His work streamlined the developer experience, reduced manual configuration, and established a foundation for future kernel-level optimizations in high-performance GPU programming environments. No bugs were reported or fixed.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
311
Activity Months1
Your Network
1366 people
Work History
October 2025
1 Commits • 1 Features
Oct 1, 2025In 2025-10 for ROCm/composable_kernel, delivered critical enhancements to support grouped GEMM preshuffle and tileloop workflows that unlock more efficient, scalable GEMM computations. Implemented tile_grouped_gemm_preshuffle support, introducing grouped_gemm_tileloop and enabling persistent mode for preshuffle in grouped GEMM. Updated tests and utility headers to accommodate the new workflow, preserving CI stability and reducing manual configuration. This work improves performance potential for grouped GEMM patterns, simplifies usage for developers, and lays groundwork for further kernel-level optimizations.
1 Commits • 1 Features
Oct 1, 2025In 2025-10 for ROCm/composable_kernel, delivered critical enhancements to support grouped GEMM preshuffle and tileloop workflows that unlock more efficient, scalable GEMM computations. Implemented tile_grouped_gemm_preshuffle support, introducing grouped_gemm_tileloop and enabling persistent mode for preshuffle in grouped GEMM. Updated tests and utility headers to accommodate the new workflow, preserving CI stability and reducing manual configuration. This work improves performance potential for grouped GEMM patterns, simplifies usage for developers, and lays groundwork for further kernel-level optimizations.
October 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
C++
Technical Skills
C++CUDA/HIPGPU ProgrammingHigh-Performance ComputingTemplate Metaprogramming
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