high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

SPH on GPU with CUDA

Alexis Herault, Giuseppe Bilotta, Robert A. Dalrymple

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Tags: CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Particle simulation, Tesla C1060

February 1, 2011 by hgpu

A Novel Monte Carlo Noise Reduction Operator

Ruifeng Xu, Sumanta N. Pattanaik

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Tags: ATI, ATI Radeon 9700, Filtering, Image processing, Package

January 30, 2011 by hgpu

Real-Time Shadow Volume Algorithm for Subdivision Surface Based Models

Min Tang, Jinxiang Dong, Shang-Ching Chou

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Tags: Algorithms, Cg, Computer science, nVidia, nVidia GeForce 6800, OpenGL, Package, Real-time graphics, Rendering

January 27, 2011 by hgpu

Efficient Parallel Scan Algorithms for GPUs

Shubhabrata Sengupta, Mark Harris, Michael Garland

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Package

January 24, 2011 by hgpu

An Improved Magma Gemm For Fermi Graphics Processing Units

Rajib Nath, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, Package, Tesla C2050

January 23, 2011 by hgpu

Swan: A tool for porting CUDA programs to OpenCL

M. J. Harvey, G. De Fabritiis

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Tags: Compilers, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C1060

January 22, 2011 by hgpu

EASEA parallelization of tree-based Genetic Programming

Ogier Maitre, S. Querry, Nicolas Lachiche and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package

January 22, 2011 by hgpu

Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single GPGPU chip

Frederic Kruger, Ogier Maitre, Santiago Jimenez, Laurent Baumes and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package, Poster

January 21, 2011 by hgpu

Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

Ogier Maitre, Nicolas Lachiche and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package, Poster

January 21, 2011 by hgpu

GP on SPMD parallel graphics hardware for mega Bioinformatics data mining

William B. Langdon, Andrew P. Harrison

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Tags: Computer science, Genetic programming, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package, RapidMind

January 21, 2011 by hgpu

Evolving GeneChip correlation predictors on parallel graphics hardware

William B. Langdon

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Tags: Bioinformatics, Computer science, Genetic programming, nVidia, nVidia GeForce 8800 GTX, OpenGL, Package, RapidMind

January 21, 2011 by hgpu

A CUDA SIMT interpreter for genetic programming. Revised

William B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, Package, Tesla T10P

January 21, 2011 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

SPH on GPU with CUDA

A Novel Monte Carlo Noise Reduction Operator

Real-Time Shadow Volume Algorithm for Subdivision Surface Based Models

Efficient Parallel Scan Algorithms for GPUs

An Improved Magma Gemm For Fermi Graphics Processing Units

Swan: A tool for porting CUDA programs to OpenCL

EASEA parallelization of tree-based Genetic Programming

Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single GPGPU chip

Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

GP on SPMD parallel graphics hardware for mega Bioinformatics data mining

Evolving GeneChip correlation predictors on parallel graphics hardware

A CUDA SIMT interpreter for genetic programming. Revised

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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