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Jingyuan Fan

PROFILE

Jingyuan Fan

During their tenure, Jfan5 enhanced FP8 quantization workflows in the ROCm/FBGEMM repository by extending quantize_fp8_row to support non-contiguous 4D tensors and updating the Triton kernel for robust, high-dimensional memory access. They addressed potential integer overflows in the mx4 quantization kernel, adding validation tests to ensure safe handling of large tensors. In pytorch/FBGEMM, Jfan5 improved build reliability by expanding CMake source discovery to include all relevant .cpp and .cu files, reducing CI failures and stabilizing integration. Their work demonstrated depth in C++, CMake, and GPU programming, focusing on reliability, maintainability, and correctness in deep learning infrastructure.

Overall Statistics

Feature vs Bugs

33%Features

Repository Contributions

4Total
Bugs
2
Commits
4
Features
1
Lines of code
305
Activity Months2

Work History

April 2025

1 Commits

Apr 1, 2025

April 2025: Focused on improving build reliability and feature completeness for pytorch/FBGEMM. Implemented broader source discovery in the CMake build to include all .cpp and .cu files under fb/src and subdirectories, addressing issues where features could be dropped during compilation. This work centers on reducing CI failures, accelerating downstream integration, and stabilizing builds for PyTorch dependencies.

December 2024

3 Commits • 1 Features

Dec 1, 2024

December 2024 ROCm/FBGEMM monthly review emphasizing robust FP8 quantization expansion and safer quantization kernels. Key work focused on delivering higher-dimensional support for FP8 quantization and hardening memory access paths in the MX4 kernel, with added tests to prevent regressions. These efforts extend device-side precision capabilities while reducing runtime risk for large-tensor workloads, directly aligning with reliability and performance goals for FP8 workflows.

Activity

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Quality Metrics

Correctness92.4%
Maintainability80.0%
Architecture75.0%
Performance75.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++CMakePython

Technical Skills

Build System ConfigurationDeep LearningGPU ComputingGPU ProgrammingMemory ManagementPyTorchQuantizationTensor OperationsTestingTriton

Repositories Contributed To

2 repos

Overview of all repositories you've contributed to across your timeline

ROCm/FBGEMM

Dec 2024 Dec 2024
1 Month active

Languages Used

C++Python

Technical Skills

Deep LearningGPU ComputingGPU ProgrammingMemory ManagementPyTorchQuantization

pytorch/FBGEMM

Apr 2025 Apr 2025
1 Month active

Languages Used

CMake

Technical Skills

Build System Configuration

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