high performance computing on graphics processing units: hgpu.org

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A Parallel Deconvolution Algorithm in Perfusion Imaging

Fan Zhu, David Rodriguez Gonzalez, Trevor Carpenter, Malcolm Atkinson, Joanna Wardlaw

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Tags: Algorithms, Biology, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Performance, Tesla C1060

November 23, 2011 by hgpu

Towards solving the Table Maker’s Dilemma on GPU

Pierre Fortin, Mourad Gouicem, Stef Graillat

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Tags: Algorithms, Computer science, CUDA, Elementary functions, nVidia, Tesla C2070

November 23, 2011 by hgpu

Accelerating Protein Sequence Search in a Heterogeneous Computing System

Shucai Xiao, Heshan Lin, Wu-chun Feng

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Tags: Algorithms, Bioinformatics, Biology, BLAST, Databases, Heterogeneous systems, nVidia, Optimization, Tesla C1060, Tesla C2050

November 23, 2011 by hgpu

An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm

Guangye Chen, Luis Chacon, Daniel C. Barnes

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Tags: Algorithms, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 580, Optimization, Particle-in-cell methods, Physics, Plasma physics

November 23, 2011 by hgpu

Application of GPGPU for Acceleration of Short DNA Sequence Alignment in Unipro UGENE Project

Konstantin Okonechinkov, German Grekhov, Konstantin Stepanyuk, Mikhail Fursov

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Tags: Algorithms, Bioinformatics, Biology, nVidia, OpenCL, Package, Sequence alignment, Tesla C1060, Tesla C2070

November 22, 2011 by hgpu

GPU-based Multi-start Local Search Algorithms

The Van Luong, Nouredine Melab, El-Ghazali Talbi

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Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 280, Optimization, Search

November 22, 2011 by hgpu

CT image reconstruction with half precision floating-point values

Clemens Maass, Sven Steckmann, Matthias Baer, Lars Hillebrand, Willi A. Kalender, Marc Kachelriess

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Tags: Algorithms, Computed tomography, CT, CUDA, Image processing, Image reconstruction, Larrabee, Medicine, nVidia, nVidia GeForce GTX 280

November 21, 2011 by hgpu

Efficient GPGPU-based parallel packet classification

Che-Lun Hung, Yaw-Ling Lin, Kuan-Ching Li, Hsiao-Hsi Wang, Shih-Wei Guo

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Tags: Algorithms, Computer science, CUDA, Filtering, Network communications, nVidia, nVidia GeForce GTS 450, Security

November 21, 2011 by hgpu

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Eugene Burmako, Rauf Sadykhov

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Tags: Algorithms, Computer science, CUDA, High-level Languages, nVidia, Package

November 21, 2011 by hgpu

Graph-based Parallel Analysis of Large Analog Circuits Based on GPU Platforms

Jianan Lu, Zhigang Hao, Sheldon X.-D. Tan

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Tags: Algorithms, CAD, Computer science, CUDA, Electronic design automation, Graph theory, nVidia, Tesla S1070

November 21, 2011 by hgpu

Efficient Stack-less BVH Traversal for Ray Tracing

Michal Hapala, Tomas Davidovic, Ingo Wald, Vlastimil Havran, Philipp Slusallek

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 260, nVidia GeForce GTX 470, Raytracing

November 20, 2011 by hgpu

Implementing a Finite Difference-Based Real-time Sound Synthesizer using GPUs

Marc Sosnick, William Hsu

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Tags: Acoustics, Algorithms, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GT 330 M, Package, Physics

November 20, 2011 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

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

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Programming

A Parallel Deconvolution Algorithm in Perfusion Imaging

Towards solving the Table Maker’s Dilemma on GPU

Accelerating Protein Sequence Search in a Heterogeneous Computing System

An efficient mixed-precision, hybrid CPU-GPU implementation of a fully implicit particle-in-cell algorithm

Application of GPGPU for Acceleration of Short DNA Sequence Alignment in Unipro UGENE Project

GPU-based Multi-start Local Search Algorithms

CT image reconstruction with half precision floating-point values

Efficient GPGPU-based parallel packet classification

Conflux: Embedding Massively Parallel Semantics in a High-Level Programming Language

Graph-based Parallel Analysis of Large Analog Circuits Based on GPU Platforms

Efficient Stack-less BVH Traversal for Ray Tracing

Implementing a Finite Difference-Based Real-time Sound Synthesizer using GPUs

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

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

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