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AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Jaber Jaber, Osama Jaber

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia B200, nVidia H100, Package, Triton

March 26, 2026 by hgpu

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Edward Lin, Sahil Modi, Siva Kumar Sastry Hari, Qijing Huang, Zhifan Ye, Nestor Qin, Fengzhe Zhou, Yuan Zhang, Jingquan Wang, Sana Damani, Dheeraj Peri, Ouye Xie, Aditya Kane, Moshe Maor, Michael Behar, Triston Cao, Rishabh Mehta, Vartika Singh, Vikram Sharma Mailthody, Terry Chen, Zihao Ye, Hanfeng Chen, Tianqi Chen, Vinod Grover, Wei Chen, Wei Liu, Eric Chung, Luis Ceze, Roger Bringmann, Cyril Zeller, Michael Lightstone, Christos Kozyrakis, Humphrey Shi

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia B200, Package, Triton

March 22, 2026 by hgpu

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Bastian Hagedorn, Alexander Collins, Tony Mongkolsmai, Vinod Grover

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Tags: Computer science, CUDA, nVidia, nVidia B200, Package, Performance, Profiling, Python, Triton

February 2, 2026 by hgpu

Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs

Rupanshu Soi, Rohan Yadav, Fredrik Kjolstad, Alex Aiken, Maryam Mehri Dehnavi, Michael Garland, Michael Bauer

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Tags: Computer science, CUDA, nVidia, nVidia B200, nVidia H100, Programming Languages

December 29, 2025 by hgpu

Accurate Models of NVIDIA Tensor Cores

Faizan A. Khattak, Mantas Mikaitis

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia B200, nVidia H100, nVidia V100, Package

December 15, 2025 by hgpu

Microbenchmarking NVIDIA’s Blackwell Architecture: An in-depth Architectural Analysis

Aaron Jarmusch, Sunita Chandrasekaran

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Tags: Benchmarking, Computer science, CUDA, HPC, Machine learning, nVidia, nVidia B200, nVidia H200, PTX

December 7, 2025 by hgpu

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Stuart H. Sul, Simran Arora, Benjamin F. Spector, Christopher Ré

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia B200, nVidia H100, Package

November 30, 2025 by hgpu

HipKittens: Fast and Furious AMD Kernels

William Hu, Drew Wadsworth, Sean Siddens, Stanley Winata, Daniel Y. Fu, Ryann Swann, Muhammad Osama, Christopher Ré, Simran Arora

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Tags: AMD Radeon Instinct MI355X, ATI, Computer science, nVidia, nVidia B200, Package, Performance

November 16, 2025 by hgpu

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

Leonardo Solis-Vasquez, Andreas F. Tillack, Diogo Santos-Martins, Andreas Koch, Stefano Forli

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Tags: Chemistry, Computer science, CUDA, Deep learning, Matrix multiplication, nVidia, nVidia A100, nVidia B200, nVidia H100, Package

October 26, 2025 by hgpu

FLASH: Fast All-to-All Communication in GPU Clusters

Yiran Lei, Dongjoo Lee, Liangyu Zhao, Daniar Kurniawan, Chanmyeong Kim, Heetaek Jeong, Changsu Kim, Hyeonseong Choi, Liangcheng Yu, Arvind Krishnamurthy, Justine Sherry, Eriko Nurvitadhi

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Tags: AMD Radeon Instinct MI300X, ATI, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia A100, nVidia B200, nVidia H100

May 25, 2025 by hgpu

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high performance computing on graphics processing units: hgpu.org

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs

Accurate Models of NVIDIA Tensor Cores

Microbenchmarking NVIDIA’s Blackwell Architecture: An in-depth Architectural Analysis

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

HipKittens: Fast and Furious AMD Kernels

Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels

FLASH: Fast All-to-All Communication in GPU Clusters

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