ROCm/aiter
Jun 2025 – Jan 2026
7 Months active
Languages Used
C++CUDAPythonAssemblyMarkdown
Technical Skills
API IntegrationC++CUDA C++CUDA ProgrammingCode RefactoringDebugging
zufayu
PROFILE
Zufayu
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
23Total
Bugs
5
Commits
23
Features
12
Lines of code
8,975
Activity Months7
Your Network
1526 people
Work History
January 2026
4 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on stabilizing the MOE FP4 prebuild workflow, expanding MHA capabilities, improving CI reliability, and documenting contribution standards for ROCm/aiter. Delivered architecture-aware scheduling for FP4 prebuilds, introduced variable-length MHA module, fixed CI-related import/formatting issues in pa_decode_gluon, and published CONTRIBUTING guidelines and setup documentation. These changes reduce prebuild failures, increase MHA flexibility and performance, improve CI reliability, and accelerate external contributions.
4 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) focused on stabilizing the MOE FP4 prebuild workflow, expanding MHA capabilities, improving CI reliability, and documenting contribution standards for ROCm/aiter. Delivered architecture-aware scheduling for FP4 prebuilds, introduced variable-length MHA module, fixed CI-related import/formatting issues in pa_decode_gluon, and published CONTRIBUTING guidelines and setup documentation. These changes reduce prebuild failures, increase MHA flexibility and performance, improve CI reliability, and accelerate external contributions.
January 2026
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 monthly summary for ROCm/aiter. Focused on stabilizing the prebuild/build system, expanding quantization capabilities, and enabling FP32 activation paths to improve reliability, performance, and scalability. Delivered three primary features with multiple fixes across commits, driving business value through faster builds, better models, and more robust deployment. Key features delivered: - Prebuild and Build System Stabilization for ROCm aiter: consolidated prebuild improvements, kernel configuration adjustments, and Torch integration tweaks across multiple commits (3cc0548..., 22122345..., ee7c1000..., 70562e8e...). Result: more reliable builds, reduced setup churn, and easier onboarding for ROCm aiter development. - NTile Configuration for A8 Block Quantization: introduced 128-ntile support for the A8 blkQ moe single-stage path, with tilesize 32x128, pertoken co bug fixes, and mem stability fixes (1127ab4b...). Result: better performance and scalability for larger data and token-based computations. - FP32 Activation Input Support and Optimizations: added FP32 input support for activation paths, with performance improvements and corrected type handling in activation and gating kernels (5c115673...). Result: improved numerical fidelity and throughput in FP32 paths. Major bugs fixed: - Addressed prebuild/attn FP8 issues and associated kernel/config bugs (e.g., prebuild=1: format and pass stability, CK updates, and module_mha_batch_prefill fixes). - Fixed multiple prebuild/compile-related bugs (ATen.h build issues, prebuild_pro_max errors, and various format/code fixes). - Resolved pertoken kernel mem faults and related performance turn issues during optimization passes. Overall impact and accomplishments: - Increased build reliability and developer productivity: fewer CI failures, faster onboarding, and more predictable local builds. - Enhanced model capability and throughput: ntile-128 A8 quantization path enables processing larger data with improved efficiency; FP32 activation path reduces precision-related edge cases and boosts performance. - Strengthened ROCm aiter ecosystem through robust prebuild, quantization, and activation paths, enabling broader adoption and more reliable production deployments. Technologies/skills demonstrated: - ROCm, aiter, prebuild automation, kernel configuration, Torch integration, CUDA/HIP interoperability. - Quantization tuning (ntile-based), pertoken and fused Moe paths, FP32 path optimization and type handling. - Cross-team collaboration and code-quality improvements across multiple commits.
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 monthly summary for ROCm/aiter. Focused on stabilizing the prebuild/build system, expanding quantization capabilities, and enabling FP32 activation paths to improve reliability, performance, and scalability. Delivered three primary features with multiple fixes across commits, driving business value through faster builds, better models, and more robust deployment. Key features delivered: - Prebuild and Build System Stabilization for ROCm aiter: consolidated prebuild improvements, kernel configuration adjustments, and Torch integration tweaks across multiple commits (3cc0548..., 22122345..., ee7c1000..., 70562e8e...). Result: more reliable builds, reduced setup churn, and easier onboarding for ROCm aiter development. - NTile Configuration for A8 Block Quantization: introduced 128-ntile support for the A8 blkQ moe single-stage path, with tilesize 32x128, pertoken co bug fixes, and mem stability fixes (1127ab4b...). Result: better performance and scalability for larger data and token-based computations. - FP32 Activation Input Support and Optimizations: added FP32 input support for activation paths, with performance improvements and corrected type handling in activation and gating kernels (5c115673...). Result: improved numerical fidelity and throughput in FP32 paths. Major bugs fixed: - Addressed prebuild/attn FP8 issues and associated kernel/config bugs (e.g., prebuild=1: format and pass stability, CK updates, and module_mha_batch_prefill fixes). - Fixed multiple prebuild/compile-related bugs (ATen.h build issues, prebuild_pro_max errors, and various format/code fixes). - Resolved pertoken kernel mem faults and related performance turn issues during optimization passes. Overall impact and accomplishments: - Increased build reliability and developer productivity: fewer CI failures, faster onboarding, and more predictable local builds. - Enhanced model capability and throughput: ntile-128 A8 quantization path enables processing larger data with improved efficiency; FP32 activation path reduces precision-related edge cases and boosts performance. - Strengthened ROCm aiter ecosystem through robust prebuild, quantization, and activation paths, enabling broader adoption and more reliable production deployments. Technologies/skills demonstrated: - ROCm, aiter, prebuild automation, kernel configuration, Torch integration, CUDA/HIP interoperability. - Quantization tuning (ntile-based), pertoken and fused Moe paths, FP32 path optimization and type handling. - Cross-team collaboration and code-quality improvements across multiple commits.
November 2025
2 Commits • 2 Features
Nov 1, 2025November 2025 (ROCm/aiter) focused on delivering performance-oriented kernel enhancements and expanding build configurability to support flexible transformer workloads. The work emphasizes measurable business value through runtime throughput improvements and faster, more versatile deployments.
2 Commits • 2 Features
Nov 1, 2025November 2025 (ROCm/aiter) focused on delivering performance-oriented kernel enhancements and expanding build configurability to support flexible transformer workloads. The work emphasizes measurable business value through runtime throughput improvements and faster, more versatile deployments.
November 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 (ROCm/aiter) focused on kernel-level performance optimizations to boost inference throughput while preserving correctness. Key delivery: a performance optimization for the scaled_act_and_mul_kernel using v_pk_mul_f32, enabling paired multiplications to increase throughput for activation/multiplication paths with correctness preserved for both paired and remaining elements. No major bugs fixed this month; minor issues were resolved as part of routine maintenance. Overall, this work improves runtime efficiency and supports higher workload throughput on ROCm-enabled devices.
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 (ROCm/aiter) focused on kernel-level performance optimizations to boost inference throughput while preserving correctness. Key delivery: a performance optimization for the scaled_act_and_mul_kernel using v_pk_mul_f32, enabling paired multiplications to increase throughput for activation/multiplication paths with correctness preserved for both paired and remaining elements. No major bugs fixed this month; minor issues were resolved as part of routine maintenance. Overall, this work improves runtime efficiency and supports higher workload throughput on ROCm-enabled devices.
August 2025
3 Commits • 1 Features
Aug 1, 2025August 2025 ROCm/aiter monthly summary focusing on reliability and data-type support. Delivered critical kernel-level precision fixes for tile-size specific (192x256 and 224x256) and Split-K paths, plus Torch.uint8 compatibility enhancements for FP4-based weight shuffling. These changes stabilize numerical results in production workloads and expand data-type support in the PyTorch integration.
3 Commits • 1 Features
Aug 1, 2025August 2025 ROCm/aiter monthly summary focusing on reliability and data-type support. Delivered critical kernel-level precision fixes for tile-size specific (192x256 and 224x256) and Split-K paths, plus Torch.uint8 compatibility enhancements for FP4-based weight shuffling. These changes stabilize numerical results in production workloads and expand data-type support in the PyTorch integration.
August 2025
July 2025
3 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for ROCm/aiter. Delivered significant A4W4 GEMM kernel enhancements with Split-K parallelism, expanded hardware support (including gfx942), and optimizations for large matrix shapes to boost GPU-accelerated matrix multiply performance. Fixed a critical bug in the split-K selection logic for the A4W4 path to ensure accurate heuristic kernel choices and stable performance. Changes shipped via two feature commits (A4w4_asm_pro (#649) and A4w4_asm_pro_max_v2 (#741)) and one targeted bug-fix commit (fix bug in splitK select (#717)). Business value: higher throughput for matrix multiply workloads, broader hardware compatibility, and more reliable kernel behavior, enabling faster time-to-insight for ML and HPC workloads. Tech skills demonstrated: CUDA/C++ kernel development, kernel selection heuristics, performance tuning for large shapes, cross-architecture support, and maintainable, commit-driven delivery.
July 2025
3 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for ROCm/aiter. Delivered significant A4W4 GEMM kernel enhancements with Split-K parallelism, expanded hardware support (including gfx942), and optimizations for large matrix shapes to boost GPU-accelerated matrix multiply performance. Fixed a critical bug in the split-K selection logic for the A4W4 path to ensure accurate heuristic kernel choices and stable performance. Changes shipped via two feature commits (A4w4_asm_pro (#649) and A4w4_asm_pro_max_v2 (#741)) and one targeted bug-fix commit (fix bug in splitK select (#717)). Business value: higher throughput for matrix multiply workloads, broader hardware compatibility, and more reliable kernel behavior, enabling faster time-to-insight for ML and HPC workloads. Tech skills demonstrated: CUDA/C++ kernel development, kernel selection heuristics, performance tuning for large shapes, cross-architecture support, and maintainable, commit-driven delivery.
June 2025
4 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for ROCm/aiter: Focused on delivering performance-oriented MoE features, stabilizing test suite, and optimizing GEMM paths. Key contributions include CK API integration in MoE EP with fused kernel optimizations, a stability fix for MoE EP tests, and a bpreshuffle option for GEMM with updated objects.
4 Commits • 2 Features
Jun 1, 2025June 2025 monthly summary for ROCm/aiter: Focused on delivering performance-oriented MoE features, stabilizing test suite, and optimizing GEMM paths. Key contributions include CK API integration in MoE EP with fused kernel optimizations, a stability fix for MoE EP tests, and a bpreshuffle option for GEMM with updated objects.
June 2025
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Quality Metrics
Correctness84.8%
Maintainability80.0%
Architecture80.0%
Performance81.4%
AI Usage28.6%
Skills & Technologies
Programming Languages
AssemblyC++CUDAMarkdownPython
Technical Skills
API IntegrationAlgorithm RefinementAssembly LanguageBuild system managementC++C++ DevelopmentC++ developmentCI/CDCUDACUDA C++CUDA KernelsCUDA ProgrammingCUDA programmingCode FormattingCode Generation
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