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Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Robert Tjarko Lange, Qi Sun, Aaditya Prasad, Maxence Faldor, Yujin Tang, David Ha

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Tags: Benchmarking, Computer science, CUDA, Filtering, LLM, nVidia, nVidia H100, Package, Software Engineering

September 21, 2025 by hgpu

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models

Siyuan Chen, Zhichao Lu, Qingfu Zhang

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Tags: Computer science, CUDA, LLM, nVidia, Software Engineering

September 21, 2025 by hgpu

Towards Calculating HPC CUDA Kernel Performance on Nvidia GPUs

Dumeni Manatschal

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce RTX 3080, Performance, PTX, Thesis

September 14, 2025 by hgpu

High Performance Matrix Multiplication

Ethan Davis

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Tags: BLAS, Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, OpenMP, Package, Performance, Python, Tesla V100

September 14, 2025 by hgpu

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software

Siddharth Samsi, Dan Campbell, Emanuel Scoullos, Oded Green

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, nVidia A100, nVidia H100, nVidia H200, Sensing

September 14, 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

CrossTL: A Universal Programming Language Translator with Unified Intermediate Representation

Nripesh Niketan, Vaatsalya Shrivastva

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Tags: Compilers, Computer science, CUDA, DirectX, GLSL, HIP, HLSL, nVidia, OpenGL, Package, Programming Languages, Vulkan

September 7, 2025 by hgpu

Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems

David Jin, Alexis Montoison, Sungho Shin

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Tags: AMD Radeon Instinct MI300X, ATI, Benchmarking, BLAS, Computer science, CUDA, Factorization, Julia, nVidia, nVidia H200, Package, ROCm

September 7, 2025 by hgpu

GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC

Chayanon Wichitrnithed, Eirik Valseth, Clint Dawson

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Tags: cfd, Computational Physics, CUDA, Data parallelism, Fluid dynamics, Fortran, MPI, nVidia, nVidia GH200, OpenACC, Package, Physics

September 7, 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

Scalable Engine and the Performance of Different LLM Models in a SLURM based HPC architecture

Anderson de Lima Luiz, Shubham Vijay Kurlekar, Munir Georges

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Tags: Computer science, Heterogeneous systems, HPC, LLM, nVidia, nVidia A100

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

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

Evolution of Kernels: Automated RISC-V Kernel Optimization with Large Language Models

Towards Calculating HPC CUDA Kernel Performance on Nvidia GPUs

High Performance Matrix Multiplication

Combining Performance and Productivity: Accelerating the Network Sensing Graph Challenge with GPUs and Commodity Data Science Software

Home-made Diffusion Model from Scratch to Hatch

CrossTL: A Universal Programming Language Translator with Unified Intermediate Representation

Harnessing Batched BLAS/LAPACK Kernels on GPUs for Parallel Solutions of Block Tridiagonal Systems

GPU-acceleration of the Discontinuous Galerkin Shallow Water Equations Solver (DG-SWEM) using CUDA and OpenACC

Managing Multi Instance GPUs for High Throughput and Energy Savings

Accelerating a Linear Programming Algorithm on AMD GPUs

Scalable Engine and the Performance of Different LLM Models in a SLURM based HPC architecture

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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