high performance computing on graphics processing units: hgpu.org

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A New Approach of Performance Analysis of Certain Graph Algorithms

M. F Mridha, Mohammad Manzurul Islam, Syed Mohammad Oliur Rahman

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Tags: Computer science, CUDA, Graph theory, nVidia, Tesla C2075

October 26, 2013 by hgpu

A Parallel Depth-aided Exemplar-based Inpainting for Real-time View Synthesis on GPU

Zheng Tian, Cheng Xu, Xiaoyun Deng

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Tags: Algorithms, Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTS 450

October 26, 2013 by hgpu

A Datalog Engine for GPUs

Carlos Alberto Martinez-Angeles, Ines Dutra, Vitor Santos Costa, Jorge Buenabad-Chavez

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 580

October 25, 2013 by hgpu

Online Performance Projection for Clusters with Heterogeneous GPUs

Lokendra S. Panwar, Ashwin M. Aji, Jiayuan Mengz, Pavan Balajiy, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, GPGPU-sim, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C1060, Tesla C2050

October 25, 2013 by hgpu

An Empirical Study of Intel Xeon Phi

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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Tags: Benchmarking, Computer science, Intel Phi, Intel Xeon Phi, Performance

October 25, 2013 by hgpu

GGAS: Global GPU Address Spaces for Efficient Communication in Heterogeneous Clusters

Lena Oden, Holger Froning

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Hybrid computing, Memory model, nVidia, nVidia Quadro 2000, nVidia Quadro FX 5800, Tesla K10, Tesla K20

October 25, 2013 by hgpu

Parallel GPU algorithms for alternate-triangular finite difference schemes

V.O. Bohaienko

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Tags: Algorithms, Computer science, Diffusion equation, Finite difference, nVidia, OpenCL, OpenMPI, Tesla M2075

October 24, 2013 by hgpu

Modeling system for GPU parallel tasks performance simulation

A.Y.Doroshenko, K.A. Zhereb, O.G.Beketov, M.V. Gnynjuk

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Tags: Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce GT 650 M, Performance

October 24, 2013 by hgpu

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

Liliana Ibeth Barbosa-Santillan, Inmaculada Alvarez-de-Mon-y-Rego

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20

October 24, 2013 by hgpu

A multi-Teraflop Constituency Parser using GPUs

John Canny, David Hall, Dan Klein

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Source codes

Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 680, Package, Tesla K10

October 24, 2013 by hgpu

Analysis of Genetic Expression with Microarrays using GPU Implemented Algorithms

Eduardo Romero-Vivas, Fernando D. Von Borstel, Isaac Villa-Medina

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9800 GT

October 24, 2013 by hgpu

A Parallel PSO Algorithm for a Watermarking Application on a GPU

Edgar Garcia Cano, Katya Rodriguez

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Tags: Algorithms, CUDA, Image processing, nVidia, Particle swarm optimization, Security, Tesla C1060

October 24, 2013 by hgpu

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

A New Approach of Performance Analysis of Certain Graph Algorithms

A Parallel Depth-aided Exemplar-based Inpainting for Real-time View Synthesis on GPU

A Datalog Engine for GPUs

Online Performance Projection for Clusters with Heterogeneous GPUs

An Empirical Study of Intel Xeon Phi

GGAS: Global GPU Address Spaces for Efficient Communication in Heterogeneous Clusters

Parallel GPU algorithms for alternate-triangular finite difference schemes

Modeling system for GPU parallel tasks performance simulation

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

A multi-Teraflop Constituency Parser using GPUs

Analysis of Genetic Expression with Microarrays using GPU Implemented Algorithms

A Parallel PSO Algorithm for a Watermarking Application on a GPU

Recent source codes

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

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

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