alibaba/rtp-llm
Nov 2024 – Jan 2025
2 Months active
Languages Used
CC++BazelPython
Technical Skills
C++C++ DevelopmentCUDADeep Learning KernelsPerformance OptimizationROCm
AMD-dteng
PROFILE
Amd-dteng
Worked on the alibaba/rtp-llm repository to deliver ROCm-optimized LayerNorm functionality for BERT models, focusing on performance and compatibility improvements. Developed a new LayerNorm2d implementation using C++ and CUDA, leveraging the composable kernel (CK) library to standardize kernel generation and streamline integration. Migrated the ROCm path to a CK_TILE-based approach, enhancing throughput and stability for Flash Attention operations. Addressed a critical bug by updating the rocmFmhaWrapper to align with the latest ck tile structure, ensuring correct handling of sequence lengths and stride propagation. Updated build systems and repository definitions to support new kernel examples and maintainability.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
4Total
Bugs
1
Commits
4
Features
2
Lines of code
1,178
Activity Months2
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1644 peopleSame Organization
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Work History
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments and business impact for the alibaba/rtp-llm repository, with emphasis on CK-based kernel generation, ROCm migration, and build/repo improvements.
2 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments and business impact for the alibaba/rtp-llm repository, with emphasis on CK-based kernel generation, ROCm migration, and build/repo improvements.
January 2025
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11 performance summary for alibaba/rtp-llm focusing on ROCm optimizations and compatibility enhancements. Delivered a ROCm-optimized LayerNorm path for BERT using a 2D kernel (LayerNorm2d) and resolved a critical bug by aligning rocmFmhaWrapper with the updated ck tile implementation for FMHA. These changes improve throughput, stability, and reliability of Flash Attention paths on ROCm, contributing to higher model efficiency in production deployments.
November 2024
2 Commits • 1 Features
Nov 1, 2024Month 2024-11 performance summary for alibaba/rtp-llm focusing on ROCm optimizations and compatibility enhancements. Delivered a ROCm-optimized LayerNorm path for BERT using a 2D kernel (LayerNorm2d) and resolved a critical bug by aligning rocmFmhaWrapper with the updated ck tile implementation for FMHA. These changes improve throughput, stability, and reliability of Flash Attention paths on ROCm, contributing to higher model efficiency in production deployments.
Activity
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Quality Metrics
Correctness82.6%
Maintainability80.0%
Architecture82.6%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BazelCC++Python
Technical Skills
Build SystemsC++C++ DevelopmentCUDACode GenerationComposable KernelDeep Learning KernelsLayer NormalizationPerformance OptimizationROCmck_tile
Repositories Contributed To
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