high performance computing on graphics processing units: hgpu.org

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Implementing Independent Component Analysis in General-Purpose GPU Architectures

Jacquelyne Forgette, Renata Wachowiak-Smolikova, Mark Wachowiak

Tags: Algorithms, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 260, OpenCL, Signal processing

September 8, 2011 by hgpu

Automatic OpenCL Device Characterization: Guiding Optimized Kernel Design

Peter Thoman, Klaus Kofler, Heiko Studt, John Thomson, Thomas Fahringer

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Benchmarking, Cell processor, Computer science, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 460, OpenCL, Optimization, Tesla C2050

September 8, 2011 by hgpu

Accelerating Clustering Coefficient Calculations on a GPU Using OPENCL

Leonid Djinevski, Igor Mishkovski, Dimitar Trajanov

Tags: Algorithms, Clustering, Computer science, Networks, OpenCL, OpenMP

September 8, 2011 by hgpu

CUDA-level performance with python-level productivity for Gaussian mixture model applications

H. Cook, E. Gonina, S. Kamil, G. Friedland, D. Patterson, A. Fox

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, OpenCL, Python

September 7, 2011 by hgpu

Towards dynamic reconfigurable load-balancing for hybrid desktop platforms

Alecio P.D. Binotto, Carlos E. Pereira, Dieter W. Fellner

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Tags: Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, OpenCL, Poster

August 31, 2011 by hgpu

Partial wave analysis at BES III harnessing the power of GPUs

Niklaus Berger

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Tags: ATI Radeon HD 4870, Brook, High Energy Physics - Experiment, nVidia, OpenCL, Physics, Statistics and Probability

August 31, 2011 by hgpu

Partial Wave Analysis using Graphics Cards

Niklaus Berger

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Tags: High Energy Physics - Experiment, nVidia, OpenCL, Physics, Statistics and Probability

August 31, 2011 by hgpu

Parallel computation of spherical parameterizations for mesh analysis

Theodoros Athanasiadis, Ioannis Fudos

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Source codes

Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package

August 24, 2011 by hgpu

Efficient implementation of GPGPU synchronization primitives on CPUs

Jayanth Gummaraju, Ben Sander, Laurent Morichetti, Benedict Gaster, Lee Howes

Tags: Computer science, OpenCL, Performance, Programming techniques

August 23, 2011 by hgpu

Top ten ways to make formal methods for HPC practical

Ganesh Gopalakrishnan, Robert M. Kirby

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Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Performance

August 22, 2011 by hgpu

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Martin Sandrieser, Siegfried Benkner, Sabri Pllana

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL, OpenMP, Presentation

August 22, 2011 by hgpu

Compiling Python to a hybrid execution environment

Rahul Garg, Jose Nelson Amaral

Tags: ATI, ATI CAL, BLAS, Compilers, Computer science, OpenCL, Python

August 21, 2011 by hgpu

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

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

See all packages

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high performance computing on graphics processing units: hgpu.org

Implementing Independent Component Analysis in General-Purpose GPU Architectures

Automatic OpenCL Device Characterization: Guiding Optimized Kernel Design

Accelerating Clustering Coefficient Calculations on a GPU Using OPENCL

CUDA-level performance with python-level productivity for Gaussian mixture model applications

Towards dynamic reconfigurable load-balancing for hybrid desktop platforms

Partial wave analysis at BES III harnessing the power of GPUs

Partial Wave Analysis using Graphics Cards

Parallel computation of spherical parameterizations for mesh analysis

Efficient implementation of GPGPU synchronization primitives on CPUs

Top ten ways to make formal methods for HPC practical

Improving programmability of heterogeneous many-core systems via explicit platform descriptions

Compiling Python to a hybrid execution environment

Recent source codes

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

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

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