pytorch/FBGEMM
Oct 2024 – Mar 2026
9 Months active
Languages Used
C++CUDAPythonCMakeShellGit
Technical Skills
C++CMakeCUDA programmingGPU computingPython scriptingBuild Systems
Li Li
PROFILE
Li Li
Worked extensively on the pytorch/FBGEMM repository, focusing on GPU kernel optimization, build system reliability, and cross-platform compatibility. Addressed performance bottlenecks in CUDA and ROCm environments by tuning kernel parameters, optimizing shared memory usage, and improving numerical stability for embedding operations. Enhanced CI/CD workflows and build robustness through targeted fixes in CMake, Python scripting, and submodule management, ensuring smoother integration with PyTorch and ROCm. Tackled issues affecting CentOS and ROCm-enabled systems, reducing build failures and test flakiness. Demonstrated depth in C++, CUDA, and Python, consistently delivering maintainable solutions that improved reliability, scalability, and hardware compatibility across diverse deployment scenarios.
Overall Statistics
Feature vs Bugs
36%Features
Repository Contributions
11Total
Bugs
7
Commits
11
Features
4
Lines of code
1,278
Activity Months9
Your Network
1756 peopleSame Organization
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Shared Repositories
195
Work History
March 2026
1 Commits
Mar 1, 2026March 2026 focused on stabilizing builds for CentOS users in pytorch/FBGEMM by fixing a TBB-related build-time error and introducing version-aware conditional compilation to support multiple TBB versions. This work improves developer experience, CI reliability, and readiness for production deployments across Linux distributions.
1 Commits
Mar 1, 2026March 2026 focused on stabilizing builds for CentOS users in pytorch/FBGEMM by fixing a TBB-related build-time error and introducing version-aware conditional compilation to support multiple TBB versions. This work improves developer experience, CI reliability, and readiness for production deployments across Linux distributions.
March 2026
December 2025
2 Commits • 2 Features
Dec 1, 2025Monthly summary for 2025-12: Key features delivered in pytorch/FBGEMM include GPU Bounds Check Kernel Performance Optimization and MI350 Backward Performance Optimization with ROCm compatibility. The bounds check optimization reduces overhead from gpuAtomicAdd by introducing shared memory to accumulate warning counts, lowering atomic frequency and boosting GPU throughput in multi-thread warning accumulation scenarios. The MI350 backward optimization tunes kernel parameters and ROCm compatibility, addressing numerical issues and enhancing embedding operation performance on MI350 hardware. These changes improve GPU throughput, reduce latency in warning checks, and broaden hardware compatibility for ROCm platforms. Technologies demonstrated include low-level GPU kernel optimization, shared memory usage, ROCm-aware tuning, and cross-team collaboration on performance-focused changes. Business value delivered includes faster kernels, improved scalability for large embeddings, and smoother deployment on AMD ROCm hardware.
December 2025
2 Commits • 2 Features
Dec 1, 2025Monthly summary for 2025-12: Key features delivered in pytorch/FBGEMM include GPU Bounds Check Kernel Performance Optimization and MI350 Backward Performance Optimization with ROCm compatibility. The bounds check optimization reduces overhead from gpuAtomicAdd by introducing shared memory to accumulate warning counts, lowering atomic frequency and boosting GPU throughput in multi-thread warning accumulation scenarios. The MI350 backward optimization tunes kernel parameters and ROCm compatibility, addressing numerical issues and enhancing embedding operation performance on MI350 hardware. These changes improve GPU throughput, reduce latency in warning checks, and broaden hardware compatibility for ROCm platforms. Technologies demonstrated include low-level GPU kernel optimization, shared memory usage, ROCm-aware tuning, and cross-team collaboration on performance-focused changes. Business value delivered includes faster kernels, improved scalability for large embeddings, and smoother deployment on AMD ROCm hardware.
October 2025
1 Commits
Oct 1, 2025Monthly summary for 2025-10: Focused on improving test reliability and ROCm compatibility in the pytorch/FBGEMM repository. No new product features deployed this month; major work centered on a targeted bug fix that stabilizes ROCm version detection in tests and lays groundwork for more robust CI. This work enhances CI reliability, reduces test flakiness, and supports broader ROCm adoption in downstream workflows.
1 Commits
Oct 1, 2025Monthly summary for 2025-10: Focused on improving test reliability and ROCm compatibility in the pytorch/FBGEMM repository. No new product features deployed this month; major work centered on a targeted bug fix that stabilizes ROCm version detection in tests and lays groundwork for more robust CI. This work enhances CI reliability, reduces test flakiness, and supports broader ROCm adoption in downstream workflows.
October 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for pytorch/FBGEMM: focused on ROCm/PyTorch compatibility for the composable_kernel submodule, delivering alignment with the ROCm repository and latest PyTorch version. This work reduces integration risk, prepares for upcoming ROCm version, and reinforces cross-ecosystem stability.
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for pytorch/FBGEMM: focused on ROCm/PyTorch compatibility for the composable_kernel submodule, delivering alignment with the ROCm repository and latest PyTorch version. This work reduces integration risk, prepares for upcoming ROCm version, and reinforces cross-ecosystem stability.
April 2025
1 Commits
Apr 1, 2025April 2025 monthly summary for pytorch/FBGEMM: Fixed build compatibility by updating the hipify_torch submodule to align with PyTorch's required CMake version, resolving issues tied to a specific PyTorch commit and ensuring stable CI and downstream integration.
1 Commits
Apr 1, 2025April 2025 monthly summary for pytorch/FBGEMM: Fixed build compatibility by updating the hipify_torch submodule to align with PyTorch's required CMake version, resolving issues tied to a specific PyTorch commit and ensuring stable CI and downstream integration.
April 2025
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for pytorch/FBGEMM focusing on deliveries, fixes, and impact across ROCm-enabled workloads. Delivered performance enhancements for quantized embedding forward passes and stabilized benchmarking visibility, driving efficiency and reliability for experimentation and production workloads.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for pytorch/FBGEMM focusing on deliveries, fixes, and impact across ROCm-enabled workloads. Delivered performance enhancements for quantized embedding forward passes and stabilized benchmarking visibility, driving efficiency and reliability for experimentation and production workloads.
January 2025
1 Commits
Jan 1, 2025January 2025 monthly summary for pytorch/FBGEMM focused on stabilizing the GPU build workflow and preserving pipeline reliability. Delivered a critical dependency fix by adding patchelf to fbgemm_gpu/requirements.txt, which unblocked the fbgemm_gpu_postbuild.bash script and the overall build process. This enables consistent artifact generation for GPU kernels and reduces CI/build failures. Commit reference: 9e9aa93465767798d7f6cf56847b6083ff061773 ("add patchelf as a required package in fbgemm_gpu/requirements.txt"; #3574).
1 Commits
Jan 1, 2025January 2025 monthly summary for pytorch/FBGEMM focused on stabilizing the GPU build workflow and preserving pipeline reliability. Delivered a critical dependency fix by adding patchelf to fbgemm_gpu/requirements.txt, which unblocked the fbgemm_gpu_postbuild.bash script and the overall build process. This enables consistent artifact generation for GPU kernels and reduces CI/build failures. Commit reference: 9e9aa93465767798d7f6cf56847b6083ff061773 ("add patchelf as a required package in fbgemm_gpu/requirements.txt"; #3574).
January 2025
November 2024
1 Commits
Nov 1, 2024November 2024 Monthly Summary — Focused on simplifying ROCm version handling in FBGEMM by centralizing the logic in the CMake build and delegating version detection to PyTorch, eliminating duplication and reducing maintenance. This work improves build reliability and reduces noise in build outputs, aligning FBGEMM with PyTorch’s single source of truth.
November 2024
1 Commits
Nov 1, 2024November 2024 Monthly Summary — Focused on simplifying ROCm version handling in FBGEMM by centralizing the logic in the CMake build and delegating version detection to PyTorch, eliminating duplication and reducing maintenance. This work improves build reliability and reduces noise in build outputs, aligning FBGEMM with PyTorch’s single source of truth.
October 2024
1 Commits
Oct 1, 2024Monthly performance summary for 2024-10 focusing on key achievements in pytorch/FBGEMM. This period delivered a critical ROCm v2 kernel compatibility fix to improve reliability and platform coverage, along with code-level improvements in CMake and templates.
1 Commits
Oct 1, 2024Monthly performance summary for 2024-10 focusing on key achievements in pytorch/FBGEMM. This period delivered a critical ROCm v2 kernel compatibility fix to improve reliability and platform coverage, along with code-level improvements in CMake and templates.
October 2024
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Quality Metrics
Correctness94.6%
Maintainability91.0%
Architecture91.0%
Performance92.8%
AI Usage21.8%
Skills & Technologies
Programming Languages
C++CMakeCUDAGitPythonShell
Technical Skills
Build System ConfigurationBuild SystemsC++C++ developmentCI/CDCMakeCUDACUDA programmingCode GenerationEmbedded SystemsGPU ProgrammingGPU computingGPU programmingLoggingNumerical Analysis
Repositories Contributed To
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