high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

M. J. Harvey, G. Giupponi, G. De Fabritiis

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Tags: Biological Physics, Chemistry, Computational Physics, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

Simulating spin models on GPU

Martin Weigel

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Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Statistical Mechanics, Tesla C1060

October 27, 2010 by hgpu

Fast fluid dynamics simulation on the GPU

Mark Harris

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Tags: Cg, Computer science, Fluid dynamics, Navier-Stokes equations, NSEs, nVidia, Package, Programming techniques

October 27, 2010 by hgpu

Monte Carlo integration on GPU

J. Kanzaki

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Monte Carlo integration, nVidia, nVidia GeForce GTX 285, Package, Physics

October 27, 2010 by hgpu

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

Benjamin Block,Peter Virnau,Tobias Preis

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Tags: CUDA, GPU cluster, Ising model, Monte Carlo simulation, nVidia, Package, Physics, Tesla C1060

October 27, 2010 by hgpu

PyCUDA: GPU Run-Time Code Generation for High-Performance Computing

Andreas Klockner,Nicolas Pinto,Yunsup Lee,Bryan Catanzaro,Paul Ivanov,Ahmed Fasih

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

October 27, 2010 by hgpu

Efficient GPU-Based Texture Interpolation using Uniform B-Splines

Daniel Ruijters,Bart ter Haar Romeny,Paul Suetens

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTX, Package

October 27, 2010 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

Applications

ACEMD: Accelerating Biomolecular Dynamics in the Microsecond Time Scale

Simulating spin models on GPU

Fast fluid dynamics simulation on the GPU

Monte Carlo integration on GPU

Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model

PyCUDA: GPU Run-Time Code Generation for High-Performance Computing

Efficient GPU-Based Texture Interpolation using Uniform B-Splines

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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