high performance computing on graphics processing units: hgpu.org

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Accelerating molecular dynamic simulation on graphics processing units

Mark S. Friedrichs, Peter Eastman, Vishal Vaidyanathan, Mike Houston, Scott Legrand, Adam L. Beberg, Daniel L. Ensign, Christopher M. Bruns, Vijay S. Pande

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Tags: ATI, ATI Radeon HD 4870, ATI Stream, Biology, Brook, Chemistry, Computational chemistry, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Solvent effects

October 30, 2010 by hgpu

A performance study of general-purpose applications on graphics processors using CUDA

S. Che, M. Boyer, J. Meng, D. Tarjan, J. Sheaffer, K. Skadron

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenMP, Package, Performance

October 30, 2010 by hgpu

GPU-based Video Feature Tracking and Matching

Sudipta N. Sinha, Jan-michael Frahm, Marc Pollefeys, Yakup Genc

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Tags: Computer science, Image processing, nVidia, nVidia GeForce 7900 GTX, OpenGL, Package, SIFT

October 29, 2010 by hgpu

The Heisenberg spin glass model on GPU: myths and actual facts

M. Bernaschi, G. Parisi, L. Parisi

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Tags: Condensed matter, CUDA, Disordered Systems and Neural Networks, nVidia, nVidia GeForce GTX 480, Package, Physics, Spin Systems, Tesla C1060, Tesla C2050

October 28, 2010 by hgpu

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

Svetlin Manavski, Giorgio Valle

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Smith-Waterman algorithm

October 28, 2010 by hgpu

GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision

Yannick Allusse, Patrick Horain, Ankit Agarwal, Cindula Saipriyadarshan

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Tags: Computer science, Computer vision, CUDA, GLSL, Image processing, nVidia, nVidia GeForce GTX 280, OpenGL, Package

October 28, 2010 by hgpu

The gputools package enables GPU computing in R

Joshua Buckner, Justin Wilson, Mark Seligman, Brian Athey, Stanley Watson, Fan Meng

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Tags: Computer science, CUBLAS, CUDA, nVidia, Package

October 28, 2010 by hgpu

High performance cellular level agent-based simulation with FLAME for the GPU

Paul Richmond, Dawn Walker, Simon Coakley, Daniela Romano

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Tags: Bioinformatics, Cellular modelling, Computational modelling, Computer science, CUDA, nVidia, Package

October 28, 2010 by hgpu

CrystalGPU: Transparent and Efficient Utilization of GPU Power

Abdullah Gharaibeh, Samer Al-Kiswany, Matei Ripeanu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GX2, Package, Performance

October 28, 2010 by hgpu

MinGPU: a minimum GPU library for computer vision

Pavel Babenko, Mubarak Shah

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Tags: Computer science, Computer vision, Homography transformation, nVidia, OpenGL, Package

October 27, 2010 by hgpu

On GPU’s viability as a middleware accelerator

Samer A. Kiswany, Abdullah Gharaibeh, Elizeu S. Neto, Matei Ripeanu

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Package, Storage system

October 27, 2010 by hgpu

Sequence alignment with GPU: Performance and design challenges

Gregory M. Striemer, Ali Akoglu

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Tags: Bioinformatics, Biology, Computational biology, Computer science, CUDA, nVidia, Package, Sequence alignment, Smith-Waterman algorithm, Tesla C870

October 27, 2010 by hgpu

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

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high performance computing on graphics processing units: hgpu.org

Accelerating molecular dynamic simulation on graphics processing units

A performance study of general-purpose applications on graphics processors using CUDA

GPU-based Video Feature Tracking and Matching

The Heisenberg spin glass model on GPU: myths and actual facts

CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment

GpuCV: A GPU-Accelerated Framework for Image Processing and Computer Vision

The gputools package enables GPU computing in R

High performance cellular level agent-based simulation with FLAME for the GPU

CrystalGPU: Transparent and Efficient Utilization of GPU Power

MinGPU: a minimum GPU library for computer vision

On GPU’s viability as a middleware accelerator

Sequence alignment with GPU: Performance and design challenges

Recent source codes

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

TRUST: a thermalhydraulic software package for CFD simulations

Modular: The Modular Platform (includes MAX & Mojo)

Allo: Accelerator Design Language

Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization

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