high performance computing on graphics processing units: hgpu.org

Packages

hgpu.org » Applications

Learning Random Forests on the GPU

Yisheng Liao, Alex Rubinsteyn, Russell Power, Jinyang Li

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX Titan, Package, Tesla C2075

December 11, 2013 by hgpu

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

P. Berczik, R. Spurzem, L. Wang, S. Zhong, O. Veles, I. Zinchenko, S. Huang, M. Tsai, G. Kennedy, S. Li, L. Naso, C. Li

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Tags: Astrophysics, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Package, Tesla C2050, Tesla K20

December 9, 2013 by hgpu

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

Xiao Zhang, Wan Guo, Xiao Qin, Xiaonan Zhao

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Tags: Chemistry, CUDA, Molecular dynamics, nVidia, Package, Tesla C2070, Tesla M2070, Tesla S1070

December 8, 2013 by hgpu

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Ricardo Javier Barrientos Rojel

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, Package, Search strategies, Tesla C1060, Tesla M2070, Thesis

December 6, 2013 by hgpu

Accelerated Event-by-Event Neutrino Oscillation Reweighting with Matter Effects on a GPU

R. G. Calland, A. C. Kaboth, D. Payne

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Tags: Computational Physics, CUDA, nVidia, nVidia GeForce GTX 670, Package, Physics, Probability

December 3, 2013 by hgpu

Exploring GPGPU Acceleration of Process-Oriented Simulations

Frederick R.M. Barnes, Thomas Pressnell, Brendan Le Foll

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Package, Programming Languages

November 26, 2013 by hgpu

Adaptive implementation selection in the SkePU skeleton programming library

Usman Dastgeer, Lu Li, Christoph Kessler

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Tags: Computer science, CUDA, Machine learning, nVidia, OpenCL, Package, Performance, Tesla C1060, Tesla C2050

November 19, 2013 by hgpu

A study of the speed and the accuracy of the Boundary Element Method as applied to the computational simulation of biological organs

Kirana Kumara P

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Tags: Computational Physics, Computer science, CUDA, Fortran, Mathematical Software, Medical Physics, MPI, nVidia, nVidia Quadro 4000, Package

November 19, 2013 by hgpu

Neurokernel: An Open Scalable Software Framework for Emulation and Validation of Drosophila Brain Models on Multiple GPUs

Lev E. Givon, Aurel A. Lazar

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Tags: Biology, CUDA, Neuroscience, nVidia, Package, Python

November 18, 2013 by hgpu

On the origin of yet another channel

Petr Svenda, Vaclav Matyas

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 465, Package, Security

November 14, 2013 by hgpu

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Michal Januszewski, Marcin Kostur

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Tags: Code generation, Computational Physics, CUDA, Fluid dynamics, Fluid simulation, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 285, OpenCL, Package, Physics, Python, Tesla C1060, Tesla C2050, Tesla K10, Tesla K20

November 12, 2013 by hgpu

Performance Evaluation of R with Intel Xeon Phi Coprocessor

Yaakoub El-Khamra, Niall Gaffney, David Walling, Eric Wernert, Weijia Xu, Hui Zhang

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Tags: Computer science, CUDA, CULA, High-level Languages, Intel Phi, Intel Xeon Phi, nVidia, Package, Performance, Tesla K20

November 12, 2013 by hgpu

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

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

Learning Random Forests on the GPU

Up to 700k GPU cores, Kepler, and the Exascale future for simulations of star clusters around black holes

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

Similarity Search in Metric Spaces on Parallel multi-core and multi-GPU Platforms

Accelerated Event-by-Event Neutrino Oscillation Reweighting with Matter Effects on a GPU

Exploring GPGPU Acceleration of Process-Oriented Simulations

Adaptive implementation selection in the SkePU skeleton programming library

A study of the speed and the accuracy of the Boundary Element Method as applied to the computational simulation of biological organs

Neurokernel: An Open Scalable Software Framework for Emulation and Validation of Drosophila Brain Models on Multiple GPUs

On the origin of yet another channel

Sailfish: a flexible multi-GPU implementation of the lattice Boltzmann method

Performance Evaluation of R with Intel Xeon Phi Coprocessor

Recent source codes

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

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

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