high performance computing on graphics processing units: hgpu.org

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Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Robert Dietrich, Thomas Ilsche, Guido Juckeland

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

April 1, 2011 by hgpu

Message Passing Interface support for the runtime adaptive multi-processor system-on-chip RAMPSoC

D. Gohringer, M. Hubner, L. Hugot-Derville, J. Becker

Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenGL

April 1, 2011 by hgpu

Higher order FEM numerical integration on GPUs with OpenCL

Przemyslaw Plaszewski, Krzysztof Banas, Pawel Maciol

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, nVidia GeForce GTX 285, OpenCL

April 1, 2011 by hgpu

Implementation of Smith-Waterman Algorithm in OpenCL for GPUs

Dzmitry Razmyslovich, Guillermo Marcus, Markus Gipp, Marc Zapatka, Andreas Szillus

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, OpenCL, Poster, Sequence alignment, Smith-Waterman algorithm

March 31, 2011 by hgpu

CUDACL: A tool for CUDA and OpenCL programmers

Ferosh Jacob, David Whittaker, Sagar Thapaliya, Purushotham Bangalore, Marjan Mernik, Jeff Gray

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Tags: Computer science, CUDA, High-level Languages, Java, nVidia, nVidia GeForce GTX 260, OpenCL

March 31, 2011 by hgpu

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

J. Breitbart, C. Fohry

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Tags: Cell processor, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenCL

March 31, 2011 by hgpu

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

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

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Source codes

Tags: Code generation, Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9400 M, nVidia GeForce GTX 295, nVidia GeForce GTX 480, OpenCL, Package, PyOpenCL, Python, Software Engineering, Tesla C1060

March 30, 2011 by hgpu

CuHMMer: A load-balanced CPU-GPU cooperative bioinformatics application

Ping Yao, Hong An, Mu Xu, Gu Liu, Xiaoqiang Li, Yaobin Wang, Wenting Han

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Pattern Search

March 29, 2011 by hgpu

Multigrid on GPU: Tackling Power Grid Analysis on parallel SIMT platforms

Zhuo Feng, Peng Li

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Tags: CAD, Computational Engineering, Computer science, CUDA, nVidia, nVidia GeForce 8800 Ultra

March 29, 2011 by hgpu

5.6: GPU enhancement of FDTD-PIC plasma-wave simulations

A.J. Woods, L.D. Ludeking

Tags: CUDA, Electrodynamics, FDTD, Finite-difference time-domain, nVidia, Plasma physics

March 29, 2011 by hgpu

Multi-mass solvers for lattice QCD on GPUs

A. Alexandru, C. Pelissier, B. Gamari, F. Lee

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Physics, QCD

March 29, 2011 by hgpu

GPU-Based Shooting and Bouncing Ray Method for Fast RCS Prediction

Yubo Tao, Hai Lin, Hujun Bao

Tags: CUDA, Electrodynamics, KD-tree, nVidia, Optics, Raytracing

March 28, 2011 by hgpu

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

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

See all packages

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high performance computing on graphics processing units: hgpu.org

Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures

Message Passing Interface support for the runtime adaptive multi-processor system-on-chip RAMPSoC

Higher order FEM numerical integration on GPUs with OpenCL

Implementation of Smith-Waterman Algorithm in OpenCL for GPUs

CUDACL: A tool for CUDA and OpenCL programmers

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

PyCUDA and PyOpenCL: A Scripting-Based Approach to GPU Run-Time Code Generation

CuHMMer: A load-balanced CPU-GPU cooperative bioinformatics application

Multigrid on GPU: Tackling Power Grid Analysis on parallel SIMT platforms

5.6: GPU enhancement of FDTD-PIC plasma-wave simulations

Multi-mass solvers for lattice QCD on GPUs

GPU-Based Shooting and Bouncing Ray Method for Fast RCS Prediction

Recent source codes

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

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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