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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

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

Peiyu Zang, Bosen Xie, Ruoxiang Xu, Yongqiang Cai

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, Package, Partial differential equations, PDEs, Physics, Triton

August 4, 2026 by hgpu

CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging

Shiyang Li, Haoyang Chen, Mattia Fazzini, Caiwen Ding

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Tags: Benchmarking, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, nVidia H200, nVidia RTX PRO 6000

May 20, 2026 by hgpu

CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe

Tara Saba, Anne Ouyang, Xujie Si, Fan Long

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Tags: Code generation, Computer science, CUDA, Machine learning, Matrix multiplication, nVidia, nVidia GeForce RTX 4090

April 13, 2026 by hgpu

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

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

Yuxuan Han, Meng-Hao Guo, Zhengning Liu, Wenguang Chen, Shi-Min Hu

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 4090, Package

March 15, 2026 by hgpu

SynPerf: A Hybrid Analytical-ML Framework for GPU Performance Prediction

Kaixuan Zhang, Yunfan Cui, Shuhao Zhang, Chutong Ding, Shiyou Qian, Luping Wang, Jian Cao, Guangtao Xue, Cheng Huang, Guodong Yang, Liping Zhang

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, nVidia A40, nVidia H100, nVidia H20, nVidia H200, nVidia H800, nVidia L20, nVidia L40, nVidia RTX 6000 Ada, Performance, Triton

January 25, 2026 by hgpu

Equivalence Checking of ML GPU Kernels

Kshitij Dubey, Benjamin Driscoll, Anjiang Wei, Neeraj Kayal, Rahul Sharma, Alex Aiken

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Tags: Computer science, CUDA, Deep learning, LLM, Machine learning, Matrix multiplication, nVidia, PTX

January 12, 2026 by hgpu

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Pierre Abillama, Changwoo Lee, Juechu Dong, David Blaauw, Dennis Sylvester, Hun-Seok Kim

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Tags: AI, Computer science, CUDA, Machine learning, Memory, nVidia, nVidia A40, nVidia Jetson Orin Nano, Package

December 29, 2025 by hgpu

AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization

Genghan Zhang, Shaowei Zhu, Anjiang Wei, Zhenyu Song, Allen Nie, Zhen Jia, Nandita Vijaykumar, Yida Wang, Kunle Olukotun

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Tags: AI, Benchmarking, Computer science, LLM, Machine learning, Performance

December 29, 2025 by hgpu

ML Inference Scheduling with Predictable Latency

Haidong Zhao, Nikolaos Georgantas

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Tags: Computer science, Machine learning, nVidia, nVidia L4, Task scheduling

December 21, 2025 by hgpu

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high performance computing on graphics processing units: hgpu.org

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

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

CUDABeaver: Benchmarking LLM-Based Automated CUDA Debugging

CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe

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

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

SynPerf: A Hybrid Analytical-ML Framework for GPU Performance Prediction

Equivalence Checking of ML GPU Kernels

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization

ML Inference Scheduling with Predictable Latency

Recent source codes

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

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