high performance computing on graphics processing units: hgpu.org

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KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Changxin Ke, Rui Zhang, Zixiang Fang, Zhenghong Li, Yuanbo Wen, Jiashuo Shen, Shuo Wang, Jiaming Guo, Ling Li, Qi Guo, Yunji Chen

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Tags: Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, Package, Triton

October 4, 2026 by hgpu

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

Devansh Jain, Akash Pardeshi, Marco Frigo, Kaustubh Khulbe, Krut Patel, Saatvik Lochan, Jai Arora, Charith Mendis

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Tags: Code generation, Compilers, Computer science, Machine learning, Package

October 4, 2026 by hgpu

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

Liam Cooper, Shinnung Jeong, Hyeran Jeon, Jeffrey Young, Hyesoon Kim

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Tags: Computer science, CUDA, Hardware Architecture, LLM, nVidia, nVidia A100, nVidia H100, nVidia L40s, Package

September 28, 2026 by hgpu

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

Li Chen

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Tags: Computer science, CUDA, LLM, nVidia, nVidia GB10, Package, Performance

September 20, 2026 by hgpu

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

Mingyuan Ma, Hu He

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Package, Programming Languages

September 20, 2026 by hgpu

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

Omkar Shewale, Deepak Kumar, Divakar Kumar Yadav

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Tags: Computer science, CUDA, LLM, nVidia, nVidia H100, Package, Performance

September 20, 2026 by hgpu

Hardware-Aware FP4 FlashAttention-4

Robert Hu

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Tags: Computer science, CUDA, nVidia, nVidia B300, nVidia GB200, Package, PTX

September 14, 2026 by hgpu

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

Zhimin Ding, Chen-Kuan Liao, Chima Adiole, Brianna Barrow, Fangzhou Du, Yu Hsiao, Ge Huang, Yicheng Jin, Ismail Syed, Chris Jermaine

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Tags: AI, Computer science, CUDA, LLM, nVidia, nVidia DGX-A100, Package, Triton

September 14, 2026 by hgpu

MaxKernel: Agentic Kernel Generation for TPUs

Shangkun Wang, Nina Cai, Charles Hoong, Julian Walker, Gerson Kroiz, George Vanica, Deepak Patil, Andi Gavrilescu, Hassan Sipra, Sethu Sankaran

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Tags: Computer science, Package, TPU

September 14, 2026 by hgpu

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

Genghan Zhang, Yixin Dong, Chengze Fan, Zhichen Zeng, Yueming Yuan, Shaowei Zhu, Kunle Olukotun

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Tags: Benchmarking, Computer science, LLM, nVidia, nVidia B200, nVidia H100, Package, PTX

August 30, 2026 by hgpu

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Jinjun Huang, Zhongzhen Wen, Tongtong Xu, Meng Yan, Xin Xia, Zhongxin Liu

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Tags: Benchmarking, Computer science, CUDA, LLM, nVidia, nVidia GeForce RTX 3090, Package, Triton

August 30, 2026 by hgpu

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high performance computing on graphics processing units: hgpu.org

Packages

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

Hardware-Aware FP4 FlashAttention-4

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

MaxKernel: Agentic Kernel Generation for TPUs

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Recent source codes

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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