ROCm/flash-attention
Nov 2024 – Jan 2026
14 Months active
Languages Used
MarkdownPythonShellYAMLC++CUDACudaTOML
Technical Skills
Build AutomationBuild SystemsCI/CDDocumentationPythonPython Development
Tri Dao
PROFILE
Tri Dao
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
323Total
Bugs
35
Commits
323
Features
139
Lines of code
87,569
Activity Months14
Your Network
45 people
Work History
January 2026
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for ROCm/flash-attention. This period focused on delivering performance-oriented features, increasing build-time flexibility, and improving code quality to support maintainability and faster iteration cycles. The work aligns with business goals to maximize GPU throughput, reduce integration risk, and enable broader CUDA platform support.
3 Commits • 2 Features
Jan 1, 2026January 2026 monthly summary for ROCm/flash-attention. This period focused on delivering performance-oriented features, increasing build-time flexibility, and improving code quality to support maintainability and faster iteration cycles. The work aligns with business goals to maximize GPU throughput, reduce integration risk, and enable broader CUDA platform support.
January 2026
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — ROCm/flash-attention: concise monthly performance summary focusing on business value and technical achievements. This period centers on integrating quack kernels as a project dependency to enable enhanced quack operations and related functionality, establishing a foundation for improved performance in attention workloads.
December 2025
1 Commits • 1 Features
Dec 1, 2025Month: 2025-12 — ROCm/flash-attention: concise monthly performance summary focusing on business value and technical achievements. This period centers on integrating quack kernels as a project dependency to enable enhanced quack operations and related functionality, establishing a foundation for improved performance in attention workloads.
November 2025
1 Commits • 1 Features
Nov 1, 2025Monthly summary for 2025-11: Focused on contributor attribution for ROCm/flash-attention. Delivered a documentation update to AUTHORS to include recent contributors, reinforcing onboarding, attribution, and governance. No major bugs fixed this month; maintenance centered on documentation and contributor experience. Impact: clearer attribution, improved onboarding for new contributors, and stronger alignment with open-source guidelines. Technologies/skills demonstrated: version control discipline, documentation best practices, contributor governance, and cross-team collaboration.
1 Commits • 1 Features
Nov 1, 2025Monthly summary for 2025-11: Focused on contributor attribution for ROCm/flash-attention. Delivered a documentation update to AUTHORS to include recent contributors, reinforcing onboarding, attribution, and governance. No major bugs fixed this month; maintenance centered on documentation and contributor experience. Impact: clearer attribution, improved onboarding for new contributors, and stronger alignment with open-source guidelines. Technologies/skills demonstrated: version control discipline, documentation best practices, contributor governance, and cross-team collaboration.
November 2025
October 2025
82 Commits • 40 Features
Oct 1, 2025October 2025 yielded a focused set of business-value outcomes for ROCm/flash-attention, combining correctness hardening, performance-oriented path optimizations, and stronger developer tooling. The team delivered across forward, backward, and postprocessing paths with an emphasis on Sm90/Sm100 variants, setting a solid baseline for continued optimization and reliability on AMD ROCm hardware.
October 2025
82 Commits • 40 Features
Oct 1, 2025October 2025 yielded a focused set of business-value outcomes for ROCm/flash-attention, combining correctness hardening, performance-oriented path optimizations, and stronger developer tooling. The team delivered across forward, backward, and postprocessing paths with an emphasis on Sm90/Sm100 variants, setting a solid baseline for continued optimization and reliability on AMD ROCm hardware.
September 2025
2 Commits • 1 Features
Sep 1, 2025Monthly summary for 2025-09 focused on ROCm/flash-attention: Delivered a feature improvement in the Cute module, refactoring exponentiation emulation and optimizing FP utilities to enhance maintainability and runtime efficiency along the critical flash-attention path. Work completed within the month with two meaningful commits that structured and clarified the emulation logic and utility code, enabling easier future changes and potential performance gains.
2 Commits • 1 Features
Sep 1, 2025Monthly summary for 2025-09 focused on ROCm/flash-attention: Delivered a feature improvement in the Cute module, refactoring exponentiation emulation and optimizing FP utilities to enhance maintainability and runtime efficiency along the critical flash-attention path. Work completed within the month with two meaningful commits that structured and clarified the emulation logic and utility code, enabling easier future changes and potential performance gains.
September 2025
August 2025
24 Commits • 8 Features
Aug 1, 2025August 2025 monthly summary for ROCm/flash-attention focused on delivering flexible model support, stability fixes, and packaging enhancements that drive deployment flexibility, throughput, and maintainability across SM90/SM100 paths. Key features and improvements were implemented with an eye toward business value: higher configurability for hidden dimensions (hdim) and Q/K/V separation, robust memory handling in sink scenarios, streamlined packaging, and modernization of core kernels. Key outcomes: - Improved configurability: Added HDIM and Q/K/V dimensionality support with stage tuning (hdim 192,128) and refactoring of q_stage, enabling customers to tailor attention dimensions for specific workloads. - Stability and correctness: Implemented sink path fixes to ensure row_max is written to shared memory and adequate smem is allocated for sScale in sink scenarios, reducing edge-case failures in streaming/inference pipelines. - Modernization and packaging: Upgraded dependencies to NVIDIA Cutlass DSL 4.1.0 and enabled flash_attn.cute as a standalone package, simplifying deployment and reproducibility. - Kernel and forward-path evolution: Ported fwd_combine kernel to cute-dsl; simplified tile scheduler storage; added Page Table with TMA and PackGQA with TMA for fwd_sm100; introduced PackGQA with TMA for fwd_sm100; advanced forward-path work (fwd_sm90) with sink, PackGQA, and R2P masking. - Lifecycle cleanup and release readiness: Removed legacy kernels and updated docs; bumped version to v2.8.3 to reflect the stable, distribution-ready release. Business impact: - Enhanced model throughput and configurability supports a wider set of deployment scenarios with lower integration risk. - Memory and kernel improvements reduce runtime variance and improve reliability in production inference. - Packaging and deprecation cleanup minimize maintenance burden and streamline downstream packaging and packaging-consumer integrations. Technologies and skills demonstrated: - CUDA/C++ kernel refactoring, cute-dsl integration, and TMA-based memory access strategies. - Cross-path optimization for fwd_sm100 and fwd_sm90 variants, including masking and sScale handling. - Dependency management, packaging engineering, and documentation stewardship.
August 2025
24 Commits • 8 Features
Aug 1, 2025August 2025 monthly summary for ROCm/flash-attention focused on delivering flexible model support, stability fixes, and packaging enhancements that drive deployment flexibility, throughput, and maintainability across SM90/SM100 paths. Key features and improvements were implemented with an eye toward business value: higher configurability for hidden dimensions (hdim) and Q/K/V separation, robust memory handling in sink scenarios, streamlined packaging, and modernization of core kernels. Key outcomes: - Improved configurability: Added HDIM and Q/K/V dimensionality support with stage tuning (hdim 192,128) and refactoring of q_stage, enabling customers to tailor attention dimensions for specific workloads. - Stability and correctness: Implemented sink path fixes to ensure row_max is written to shared memory and adequate smem is allocated for sScale in sink scenarios, reducing edge-case failures in streaming/inference pipelines. - Modernization and packaging: Upgraded dependencies to NVIDIA Cutlass DSL 4.1.0 and enabled flash_attn.cute as a standalone package, simplifying deployment and reproducibility. - Kernel and forward-path evolution: Ported fwd_combine kernel to cute-dsl; simplified tile scheduler storage; added Page Table with TMA and PackGQA with TMA for fwd_sm100; introduced PackGQA with TMA for fwd_sm100; advanced forward-path work (fwd_sm90) with sink, PackGQA, and R2P masking. - Lifecycle cleanup and release readiness: Removed legacy kernels and updated docs; bumped version to v2.8.3 to reflect the stable, distribution-ready release. Business impact: - Enhanced model throughput and configurability supports a wider set of deployment scenarios with lower integration risk. - Memory and kernel improvements reduce runtime variance and improve reliability in production inference. - Packaging and deprecation cleanup minimize maintenance burden and streamline downstream packaging and packaging-consumer integrations. Technologies and skills demonstrated: - CUDA/C++ kernel refactoring, cute-dsl integration, and TMA-based memory access strategies. - Cross-path optimization for fwd_sm100 and fwd_sm90 variants, including masking and sScale handling. - Dependency management, packaging engineering, and documentation stewardship.
July 2025
40 Commits • 16 Features
Jul 1, 2025July 2025 monthly summary for ROCm/flash-attention focusing on business value, feature delivery, and robust performance improvements.
40 Commits • 16 Features
Jul 1, 2025July 2025 monthly summary for ROCm/flash-attention focusing on business value, feature delivery, and robust performance improvements.
July 2025
June 2025
32 Commits • 15 Features
Jun 1, 2025June 2025 performance summary for ROCm/flash-attention. The month focused on delivering key features, improving reliability, and accelerating performance across the Cute compute path and Sm80/Sm90 architectures, while expanding test coverage and CI reliability. Contributions span code quality, feature delivery, optimization, and governance enhancements, collectively enabling broader hardware support and faster time-to-value for customers.
June 2025
32 Commits • 15 Features
Jun 1, 2025June 2025 performance summary for ROCm/flash-attention. The month focused on delivering key features, improving reliability, and accelerating performance across the Cute compute path and Sm80/Sm90 architectures, while expanding test coverage and CI reliability. Contributions span code quality, feature delivery, optimization, and governance enhancements, collectively enabling broader hardware support and faster time-to-value for customers.
April 2025
26 Commits • 10 Features
Apr 1, 2025April 2025 performance summary for ROCm/flash-attention: delivered substantial feature work and stability improvements across attention, rotary kernels, and LayerNorm, with broad compiler and CI enhancements. Notable outcomes include new tests for attention_chunk and kvcache with non-causal support and precomputed metadata, rotary kernel tuning for small rotary_dim and cross-dimension tiling via Triton 3.x, and LayerNorm and scheduling optimizations that improved throughput and stability. CI/toolchain updates (dropping older PyTorch versions and updating NVCC) reduced build risk and improved release readiness. Targeted bug fixes and refactors improved correctness and maintainability, including import error fixes and interface cleanups.
26 Commits • 10 Features
Apr 1, 2025April 2025 performance summary for ROCm/flash-attention: delivered substantial feature work and stability improvements across attention, rotary kernels, and LayerNorm, with broad compiler and CI enhancements. Notable outcomes include new tests for attention_chunk and kvcache with non-causal support and precomputed metadata, rotary kernel tuning for small rotary_dim and cross-dimension tiling via Triton 3.x, and LayerNorm and scheduling optimizations that improved throughput and stability. CI/toolchain updates (dropping older PyTorch versions and updating NVCC) reduced build risk and improved release readiness. Targeted bug fixes and refactors improved correctness and maintainability, including import error fixes and interface cleanups.
April 2025
March 2025
33 Commits • 14 Features
Mar 1, 2025March 2025 monthly summary for ROCm/flash-attention focusing on delivering targeted kernel optimizations, improved scheduling/metadata flow, and broader hardware/tooling support. The month combined refactors that streamline memory access and output paths with performance-driven kernel tiling and batch-aware execution, along with tooling and benchmark updates to ensure robust measurements and compatibility. Several correctness and stability fixes were implemented to ensure production readiness on ROCm platforms, alongside expanded backends and kernel features that unlock higher throughput for large-scale attention workloads.
March 2025
33 Commits • 14 Features
Mar 1, 2025March 2025 monthly summary for ROCm/flash-attention focusing on delivering targeted kernel optimizations, improved scheduling/metadata flow, and broader hardware/tooling support. The month combined refactors that streamline memory access and output paths with performance-driven kernel tiling and batch-aware execution, along with tooling and benchmark updates to ensure robust measurements and compatibility. Several correctness and stability fixes were implemented to ensure production readiness on ROCm platforms, alongside expanded backends and kernel features that unlock higher throughput for large-scale attention workloads.
February 2025
39 Commits • 19 Features
Feb 1, 2025February 2025 monthly summary for ROCm/flash-attention: delivered advanced HeadDim_V vs HeadDim_QK support, stabilized FP8 paths, and drove performance, reliability, and maintainability improvements across the project. This period also strengthened benchmarking, toolchain alignment, and testing coverage to enable robust production readiness.
39 Commits • 19 Features
Feb 1, 2025February 2025 monthly summary for ROCm/flash-attention: delivered advanced HeadDim_V vs HeadDim_QK support, stabilized FP8 paths, and drove performance, reliability, and maintainability improvements across the project. This period also strengthened benchmarking, toolchain alignment, and testing coverage to enable robust production readiness.
February 2025
January 2025
24 Commits • 10 Features
Jan 1, 2025January 2025 performance summary for ROCm/flash-attention. Delivered a major core refactor and baseline updates, extensive cross-architecture compilation and tuning for Sm80/Sm90/Sm86, and PackGQA-driven optimizations to reduce binary size and compile time. Achieved broader hardware coverage, improved runtime performance, and aligned the project with modern toolchains (nvcc 12.8) and build policies (drop CUDA 11, PyTorch 2.1 removal). Stability improvements address mem fence issues and key correctness checks, contributing to reliability across configurations.
January 2025
24 Commits • 10 Features
Jan 1, 2025January 2025 performance summary for ROCm/flash-attention. Delivered a major core refactor and baseline updates, extensive cross-architecture compilation and tuning for Sm80/Sm90/Sm86, and PackGQA-driven optimizations to reduce binary size and compile time. Achieved broader hardware coverage, improved runtime performance, and aligned the project with modern toolchains (nvcc 12.8) and build policies (drop CUDA 11, PyTorch 2.1 removal). Stability improvements address mem fence issues and key correctness checks, contributing to reliability across configurations.
December 2024
10 Commits
Dec 1, 2024Month 2024-12 – ROCm/flash-attention: Consolidated build and compatibility stabilization across PyTorch 2.x and CUDA variants. Completed in-repo compatibility fixes and CI enhancements to ensure Flash Attention compiles and runs on PyTorch 2.x (including 2.6 dev) and CUDA variants, with updated dependencies and simplified include paths. The work includes header adjustments for Philox, Cutlass 3.6 compatibility, and nvcc-related settings, plus bumps to the flash-attention library to align with releases. This provides a robust foundation for adoption by users upgrading PyTorch/CUDA and reduces maintenance burden for future releases.
10 Commits
Dec 1, 2024Month 2024-12 – ROCm/flash-attention: Consolidated build and compatibility stabilization across PyTorch 2.x and CUDA variants. Completed in-repo compatibility fixes and CI enhancements to ensure Flash Attention compiles and runs on PyTorch 2.x (including 2.6 dev) and CUDA variants, with updated dependencies and simplified include paths. The work includes header adjustments for Philox, Cutlass 3.6 compatibility, and nvcc-related settings, plus bumps to the flash-attention library to align with releases. This provides a robust foundation for adoption by users upgrading PyTorch/CUDA and reduces maintenance burden for future releases.
December 2024
November 2024
6 Commits • 2 Features
Nov 1, 20242024-11 monthly summary focusing on stability, release readiness, and documentation for ROCm/flash-attention. Focused on CI/environment reliability and product readiness for downstream integration, culminating in a formal release (v2.7.0) and updated FA3 documentation.
November 2024
6 Commits • 2 Features
Nov 1, 20242024-11 monthly summary focusing on stability, release readiness, and documentation for ROCm/flash-attention. Focused on CI/environment reliability and product readiness for downstream integration, culminating in a formal release (v2.7.0) and updated FA3 documentation.
Activity
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Quality Metrics
Correctness89.2%
Maintainability85.6%
Architecture87.2%
Performance85.4%
AI Usage21.8%
Skills & Technologies
Programming Languages
AssemblyC++CUDACudaMarkdownPlain TextPythonShellTOMLYAML
Technical Skills
API DesignAPI IntegrationAlgorithm OptimizationAlgorithm optimizationAssemblyAssembly LanguageAsynchronous OperationsAsynchronous ProgrammingAttention MechanismsAttention mechanismsBackend DevelopmentBenchmarkingBit ManipulationBug FixBuild Automation
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