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Jeff Huang

PROFILE

Jeff Huang

Worked on ROCm/composable_kernel and ROCm/aiter, focusing on enhancing kernel robustness, memory safety, and scalability for large-scale transformer workloads. Developed and optimized batch prefill kernels in C++ and CUDA, introducing memory-layout decoupling, support for large key-value caches, and configurable cache layouts to improve throughput and reliability. Addressed critical GPU memory access faults and numerical stability issues, implementing regression tests and validation across multiple GPU architectures. Leveraged parallel computing and performance optimization techniques to support long-context inference and FP8 workloads. Collaborated on cross-repository submodule alignment, ensuring consistent interfaces and safer production deployments for attention-based machine learning kernels.

Overall Statistics

Feature vs Bugs

43%Features

Repository Contributions

11Total
Bugs
4
Commits
11
Features
3
Lines of code
4,074
Activity Months4

Work History

May 2026

2 Commits

May 1, 2026

May 2026: Strengthened reliability and correctness of memory-prefetch paths across ROCm/composable_kernel and ROCm/aiter, delivering critical fixes, expanded test coverage, and alignment of submodules. Key outcomes include robust fixes for GPU memory access faults in mha_batch_prefill and out-of-bounds (OOB) page table reads, along with comprehensive regression tests and cross-GPU validation. The changes reduce risk of memory violations and silent data corruption in high-seqlen configurations and large KV caches, enabling safer production workloads for attention-based kernels. Submodule alignment (composable_kernel) to rocm-libraries#6932 ensures consistency across components. This work demonstrates strong kernel-level memory-safety expertise, regression testing, HIP/VMM tooling, and cross-repo collaboration, improving stability, correctness, and developer velocity for next-gen FMHA and KV-cache scenarios.

April 2026

2 Commits • 1 Features

Apr 1, 2026

April 2026 monthly summary for ROCm/composable_kernel: Delivered robust KV cache prefill support for long-context inference by enabling KV caches >2GB with a two-mode dispatch system. Temporarily removed overflow assertions to unblock progress, with a plan for a proper overflow handling fix in a follow-up PR. Implemented template-driven path selection and per-tile SRD rebase trimming to support large-page and small-page regimes across gfx architectures (CDNA3/CDNA4). Verified across architectures with a comprehensive test suite, including 96-case functional matrix and >2GB KV cache tests; all tests passed on MI308 (gfx942) and MI355 (gfx950). Performance analysis shows a ~2.7% kernel-time increase on the gfx950 hot path due to necessary correctness guards, with no regressions on gfx942. Overall impact: improved robustness, scalability, and ability to handle longer-context workloads, delivering clear business value by enabling longer inputs and more scalable KV caching.

March 2026

2 Commits • 1 Features

Mar 1, 2026

March 2026 monthly performance summary for ROCm/composable_kernel. Focused on reliability, scalability, and FP8 path improvements that directly enhance model capacity and production throughput. The work delivered two high-impact items: a critical bug fix addressing 32-bit overflow in batch prefill for very large key-value caches, and a feature enabling FP8 batch prefill support for head_dim=256, with codegen changes and validated cross-platform tests.

January 2026

5 Commits • 1 Features

Jan 1, 2026

January 2026 performance summary for ROCm/composable_kernel focusing on FMHA batch prefill enhancements and numerical stability fixes. Delivered substantial batch prefill kernel improvements with memory-layout decoupling and support for multiple page sizes and layouts, along with a critical stability patch for FMHA QRKSVS pipeline. Established groundwork for configurable KV cache layouts and codegen-driven optimizations, improving throughput, memory efficiency, and reliability of large-scale transformer workloads.

Activity

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Quality Metrics

Correctness89.0%
Maintainability81.8%
Architecture87.2%
Performance80.0%
AI Usage29.0%

Skills & Technologies

Programming Languages

C++Python

Technical Skills

Algorithm DesignAlgorithm OptimizationC++ developmentC++ programmingCUDAData StructuresGPU ProgrammingGPU programmingKernel DevelopmentMachine LearningParallel ComputingPerformance OptimizationPython DevelopmentTestingalgorithm optimization

Repositories Contributed To

2 repos

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

ROCm/composable_kernel

Jan 2026 May 2026
4 Months active

Languages Used

C++Python

Technical Skills

Algorithm DesignAlgorithm OptimizationC++ developmentC++ programmingCUDAData Structures

ROCm/aiter

May 2026 May 2026
1 Month active

Languages Used

C++Python

Technical Skills

CUDAGPU ProgrammingPython DevelopmentTesting