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KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

Qitong Sun, Jun Han, Tianlin Li, Zhe Tang, Sheng Chen, Fei Yang, Aishan Liu, Xianglong Liu, Yang Liu

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Tags: Computer science, CUDA, LLM, nVidia, nVidia A100, Package, Performance, PyTorch

March 15, 2026 by hgpu

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

Jinwu Chen, Qidie Wu, Bin Li, Lin Ma, Xin Si, Yang Hu, Shouyi Yin, Jun Yang

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Tags: AI, Code generation, Computer science, CUDA, nVidia, nVidia A100, Package, PyTorch

December 21, 2025 by hgpu

PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks & Fast Storage

Jigao Luo, Nils Boeschen, Muhammad El-Hindi, Carsten Binnig

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Tags: Computer science, CUDA, Databases, GPU cluster, nVidia, nVidia A100, nVidia DGX-1, PyTorch

December 21, 2025 by hgpu

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

Haonan Li, Keyu Man, Partha Kanuparthy, Hanning Chen, Wei Sun, Sreen Tallam, Chenguang Zhu, Kevin Zhu, Zhiyun Qian

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

December 15, 2025 by hgpu

Accelerating Molecular Simulations with Triton: Fused GPU Kernels for TensorNet Neural Potentials

Manpreet Singh

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Tags: Biology, Chemistry, CUDA, Molecular dynamics, nVidia, nVidia A100, PyTorch, Triton

December 15, 2025 by hgpu

Decoupled Triton: A Block-Level Decoupled Language for Writing and Exploring Efficient Machine-Learning Kernels

Quinn Leo Pham

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Tags: Compilers, Computer science, Machine learning, nVidia, nVidia RTX 5000 Ada, PyTorch, Thesis, Triton

December 7, 2025 by hgpu

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

Marcin Spoczynski, Marcela S. Melara

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Tags: Computer science, Machine learning, nVidia, oneAPI, Package, PyTorch, Rust, Security, SYCL

November 2, 2025 by hgpu

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Zhongzhen Wen, Hongyu Liu, Tingwei Zhu, Minxue Pan, Shaohua Wang, Yuanyi Lin, Kairui Liu, Tian Zhang, Xuandong Li

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Tags: Computer science, CUDA, Deep learning, nVidia, Package, PyTorch

November 2, 2025 by hgpu

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models

Ping Guo, Chenyu Zhu, Siyuan Chen, Fei Liu, Xi Lin, Zhichao Lu, Qingfu Zhang

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Tags: AI, Code generation, Computer science, CUDA, Deep learning, LLM, nVidia, nVidia GeForce RTX 4090, nVidia H100, PyTorch

October 12, 2025 by hgpu

Home-made Diffusion Model from Scratch to Hatch

Shih-Ying Yeh

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce RTX 5090, Package, Python, PyTorch

September 14, 2025 by hgpu

Managing Multi Instance GPUs for High Throughput and Energy Savings

Abhijeet Saraha, Yuanbo Li, Chris Porter, Santosh Pande

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Tags: Computer science, CUDA, Energy-efficient computing, LLM, nVidia, nVidia A100, PyTorch, Security

September 7, 2025 by hgpu

Accelerating a Linear Programming Algorithm on AMD GPUs

Xiyan Hu, Titus Parker, Connor Phillips, Yifa Yu

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Tags: AMD Radeon Instinct MI210, AMD Radeon Instinct MI325X, ATI, Computer science, HIP, nVidia, nVidia A100, Package, Performance, PyTorch, ROCm, Thesis

August 31, 2025 by hgpu

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

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

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

RepoLaunch: Automating Build & Test Pipeline of Code Repositories on ANY Language and ANY Platform

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high performance computing on graphics processing units: hgpu.org

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

PystachIO: Efficient Distributed GPU Query Processing with PyTorch over Fast Networks & Fast Storage

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

Accelerating Molecular Simulations with Triton: Fused GPU Kernels for TensorNet Neural Potentials

Decoupled Triton: A Block-Level Decoupled Language for Writing and Exploring Efficient Machine-Learning Kernels

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models

Home-made Diffusion Model from Scratch to Hatch

Managing Multi Instance GPUs for High Throughput and Energy Savings

Accelerating a Linear Programming Algorithm on AMD GPUs

Recent source codes

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

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

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

MSKernelBench & CUDAMaster

EvoScientist: Harness Vibe Research with Self-evolving AI Scientists

RepoLaunch: Automating Build and Test Pipeline of Code Repositories on ANY Language and ANY Platform

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