high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Pipelining the Fast Multipole Method over a Runtime System

Emmanuel Agullo, Beranger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Takahashi Toru

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Tags: Algorithms, Computer science, Fast multipole method, Heterogeneous systems, nVidia, Physics, Tesla M2070, Tesla M2090

June 4, 2012 by hgpu

GPU Join Processing Revisited

Tim Kaldewey, Guy Lohman, Rene Mueller, Peter Volk

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 580

June 3, 2012 by hgpu

Parallel Triangular Solvers on GPU

Hui Liu, Song Yu, Zhangxin Chen

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla C2050, Tesla C2070

June 3, 2012 by hgpu

Parallel Agent systems on a GPU for use with Simulations and Games

Timothy Johnson, John Rankin

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Tags: Computer science, Games, nVidia, nVidia GeForce GT 220 M, OpenCL

June 3, 2012 by hgpu

Reservoir Simulation on NVIDIA Tesla GPUs

Zhangxin Chen, Hui Liu, Song Yu, Ben Hsieh, Lei Shao

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Tags: Computer science, nVidia, Tesla C2050, Tesla C2070

June 3, 2012 by hgpu

Towards Distributed Heterogenous High-Performance Computing with ViennaCL

Josef Weinbub, Karl Rupp, Siegfried Selberherr

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Tags: Benchmarking, Computer science, Distributed computing, MPI, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, OpenCL, Package, Tesla C2050

June 1, 2012 by hgpu

MPI-ACC: An Integrated and Extensible Approach to Data Movement in Accelerator-Based Systems

Ashwin M. Aji, James Dinan, Darius Buntinas, Pavan Balaji, Wu-chun Feng, Keith R. Bisset, Rajeev Thakur

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Tags: Computer science, CUDA, GPU cluster, MPI, nVidia, Tesla C2050

June 1, 2012 by hgpu

A Data-Parallel Extension to Ruby for GPGPU

Hidehiko Masuhara, Yusuke Nishiguchi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 465, Package, Programming Languages

June 1, 2012 by hgpu

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

Bor-Yiing Su, Kurt Keutzer

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Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sparse matrix

May 30, 2012 by hgpu

X-Device Query Processing by Bitwise Distribution

Holger Pirk, Thibault Sellam, Stefan Manegold, Martin Kersten

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

May 30, 2012 by hgpu

COVRA: A compression-domain output-sensitive volume rendering architecture based on a sparse representation of voxel blocks

Enrico Gobbetti, Jose Antonio Iglesias Guitian, Fabio Marton

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Tags: 3D Graphics and Realism, Algorithms, Compression, Computer science, Filtering, Image generation, nVidia, nVidia GeForce GTX 560, OpenGL, Rendering

May 29, 2012 by hgpu

A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

Philippe Estival, Luc Giraud

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, Tesla T10

May 29, 2012 by hgpu

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

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

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

CONCUR: Benchmarking LLMs for Concurrent Code Generation

HIPRT: Ray Tracing using HIP

Ray Tracing using HIP

MXFP4 Training Support Codebase

Practical FP4 Training for Large-Scale MoE Models on Hopper GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Pipelining the Fast Multipole Method over a Runtime System

GPU Join Processing Revisited

Parallel Triangular Solvers on GPU

Parallel Agent systems on a GPU for use with Simulations and Games

Reservoir Simulation on NVIDIA Tesla GPUs

Towards Distributed Heterogenous High-Performance Computing with ViennaCL

MPI-ACC: An Integrated and Extensible Approach to Data Movement in Accelerator-Based Systems

A Data-Parallel Extension to Ruby for GPGPU

clSpMV: A Cross-Platform OpenCL SpMV Framework on GPUs

X-Device Query Processing by Bitwise Distribution

COVRA: A compression-domain output-sensitive volume rendering architecture based on a sparse representation of voxel blocks

A fight for performance and accuracy of the matrix multiplication routines: CUBLAS on Nvidia Tesla versus MKL and ATLAS on Intel Nehalem

Recent source codes

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

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

CONCUR: a benchmark designed to evaluate multithreaded Java code generated by LLMs

HIPRT: Ray Tracing using HIP

MXFP4 Training Support Codebase

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