ROCm/pytorch
Sep 2025 – Sep 2025
1 Month active
Languages Used
C++
Technical Skills
CUDA programmingDebuggingPerformance optimization
Michael Kelly
PROFILE
Michael Kelly
Over a two-month period, Michael K. developed and stabilized advanced debugging tools for CUDA kernels in the ROCm/pytorch and pytorch/pytorch repositories. He introduced the CUDA_KERNEL_ASSERT_PRINTF helper, which merges printf-style diagnostics with assertions to provide device-side context in error messages, reducing the need for recompilation and reruns during kernel debugging. Using C++, CUDA, and Python, Michael ensured performance sensitivity by gating printf usage in critical paths. He also improved error reporting and index bounds validation for vectorized gather kernels, reinstating format-string arguments and implementing robust sanity checks, which enhanced reliability and traceability across CUDA and CPU workflows.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
2Total
Bugs
1
Commits
2
Features
1
Lines of code
53
Activity Months2
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Work History
December 2025
1 Commits
Dec 1, 2025Month 2025-12: Stabilized the vectorized gather path in pytorch/pytorch by fixing error reporting and index bounds validation. Reinstated missing format-string arguments in CUDA_KERNEL_ASSERT_VERBOSE (IndexKernelUtils.cu) to improve debugging for vectorized gather kernels, aligned with PR #170913 and D89575112. Executed sanity checks to prevent grid-config regressions and validated results across CUDA kernels and CPU.
1 Commits
Dec 1, 2025Month 2025-12: Stabilized the vectorized gather path in pytorch/pytorch by fixing error reporting and index bounds validation. Reinstated missing format-string arguments in CUDA_KERNEL_ASSERT_VERBOSE (IndexKernelUtils.cu) to improve debugging for vectorized gather kernels, aligned with PR #170913 and D89575112. Executed sanity checks to prevent grid-config regressions and validated results across CUDA kernels and CPU.
December 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a new CUDA_KERNEL_ASSERT_PRINTF helper for CUDA kernel debugging in ROCm/pytorch. This feature combines printf-style diagnostics with assertions to provide device-side context in error messages, improving developer experience by reducing the need to recompile and re-run workflows. The changes maintain performance sensitivity by avoiding printf calls in critical paths and complement the existing CUDA_KERNEL_ASSERT_MSG macro, enabling richer, faster-to-diagnose kernel failures.
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025: Delivered a new CUDA_KERNEL_ASSERT_PRINTF helper for CUDA kernel debugging in ROCm/pytorch. This feature combines printf-style diagnostics with assertions to provide device-side context in error messages, improving developer experience by reducing the need to recompile and re-run workflows. The changes maintain performance sensitivity by avoiding printf calls in critical paths and complement the existing CUDA_KERNEL_ASSERT_MSG macro, enabling richer, faster-to-diagnose kernel failures.
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage30.0%
Skills & Technologies
Programming Languages
C++CUDAPython
Technical Skills
CUDA programmingDebuggingGPU computingPerformance optimization
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline
pytorch/pytorch
Dec 2025 – Dec 2025
1 Month active
Languages Used
CUDAPython
Technical Skills
CUDA programmingDebuggingGPU computing