December 2025 monthly performance summary for ROCm/composable_kernel. Focused on delivering high-value performance and reliability improvements for convolution and GEMM kernels, with an emphasis on grouped convolutions and tile-based execution paths. Achievements span performance optimizations, correctness fixes, and robustness enhancements that reduce latency and improve scalability across workloads that rely on backward data/weight convolutions and tiled GEMM. These workstreams support stronger throughput for deep learning workloads and better resource utilization on real hardware.

October 2025 monthly summary for ROCm/composable_kernel: Delivered a performance-focused optimization by integrating universal GEMM paths into the grouped convolution kernels. Refactored the grouped convolution workflow to use universal GEMMs for backward data and weight computations, and extended support to include forward computations. Implemented new GEMM configurations and updated tensor descriptor transformations and kernel argument handling to align with the universal GEMM pipelines. The changes are driven by a key commit to switch conv backward paths to universal GEMMs and to enable universal GEMM support in conv forward, establishing groundwork for improved performance and flexibility.

September 2025: Delivered a Two-Stage Backward Weight Computation feature for grouped convolutions in CK_TILE within ROCm/composable_kernel. This work included kernel refactors, new invoker/kernel files to support the two-stage approach, and build-system integration via CMakeLists.txt and header updates to ensure cohesive usage across the CK_TILE pathway. The change broadens CK_TILE’s applicability for grouped convolutions and positions the codebase for future performance tuning and optimization passes. Minor post-review fixes were incorporated as part of the feature work. All changes were integrated with the ROCm/composable_kernel repository under collaborative review, including co-authorship acknowledgments.

July 2025 monthly summary focused on delivering essential kernel capability enhancements to the ROCm-based libraries and strengthening the composable kernel ecosystem.

May 2025 monthly summary focused on ROCm-based GEMM epilogue improvements in the StreamHPC/rocm-libraries repository. Delivered configurable memory operation handling by introducing a new memory_operation parameter and removing scratch memory usage in the GEMM epilogue path, enabling the kernel to choose between set or atomic_add based on batch size for better efficiency and scalability. This work reduces memory footprint, simplifies epilogue memory semantics, and improves predictability across workloads.

April 2025 performance summary for StreamHPC/rocm-libraries focused on features delivered, packaging improvements, and readiness for sparse matrix workloads.

In March 2025, delivered a performance-focused refactor of the GEMM pipeline in StreamHPC/rocm-libraries to support universal GEMM across batched and grouped workloads. The changes introduce a single, configurable pipeline with new configurations and tuned kernel parameters, enabling better performance and flexibility across GPU kernels. This refactor reduces maintenance overhead and sets the stage for further optimizations across the ROCm libraries.

February 2025 monthly summary for StreamHPC/rocm-libraries focusing on GEMM kernel optimizations and memory pipeline robustness.

December 2024 monthly summary for StreamHPC/rocm-libraries highlighting feature delivery, validation enhancements, and testing improvements that increase reliability and reduce production risk.

Month: 2024-11 — StreamHPC/rocm-libraries: Delivered two key GEMM improvements focused on reliability, performance, and test coverage. Implemented guard logic for bf16 splitk support in grouped GEMM and introduced an Interwave scheduler to optimize the GEMM memory pipeline, accompanied by refactoring and updated tests to validate stability and performance.