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Yuankun Shi

PROFILE

Yuankun Shi

Developed and integrated a new GEMM post-processing step called 'splitk' within the intel/sycl-tla repository, enabling the output tensor to be divided into two distinct parts, 'nope' and 'rope', based on configurable dimensions. This feature allows for specialized downstream handling and opens opportunities for targeted optimizations in high-performance tensor workflows. The implementation leveraged C++, SYCL, and CMake, focusing on modularity and alignment with the project’s performance roadmap. By tracking the work under a dedicated issue, the developer ensured clear documentation and roadmap alignment, laying the groundwork for future enhancements in GPU programming and high-performance computing environments.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

1Total
Bugs
0
Commits
1
Features
1
Lines of code
902
Activity Months1

Work History

May 2025

1 Commits • 1 Features

May 1, 2025

Month: 2025-05. Focused on delivering a new GEMM post-processing step 'splitk' in intel/sycl-tla to split GEMM outputs into two parts, 'nope' and 'rope', based on specified dimensions. This enables distinct downstream handling and potential optimization opportunities within tensor workflows. The work centers on feature delivery with code integration and roadmap alignment for performance-oriented tensor pipelines.

Activity

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Quality Metrics

Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%

Skills & Technologies

Programming Languages

C++CMake

Technical Skills

CUTLASSGEMMGPU ProgrammingHigh-Performance ComputingSYCL

Repositories Contributed To

1 repo

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

intel/sycl-tla

May 2025 May 2025
1 Month active

Languages Used

C++CMake

Technical Skills

CUTLASSGEMMGPU ProgrammingHigh-Performance ComputingSYCL