high performance computing on graphics processing units: hgpu.org

Programming

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Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

Alexander Ross Mace

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Tags: Biology, Computer science, Monte Carlo simulation, OpenCL, Probability, Thesis

July 3, 2015 by hgpu

GPU phase-field lattice Boltzmann simulations of growth and motion of a binary alloy dendrite

T. Takaki, R. Rojas, M Ohno, T. Shimokawabe, T. Aoki

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Tags: Alloys, Condensed matter, CUDA, Lattice Boltzmann model, Materials Science, nVidia, Physics, Tesla K20

July 3, 2015 by hgpu

Parallel Sparse Coding for Seafloor Image Analysis

Genlang Chen, Chenggang Lai, Miaoqing Huang

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Tags: CUDA, Image processing, Intel Xeon Phi, Machine learning, nVidia, Tesla K20

July 3, 2015 by hgpu

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Andrea Miele

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan Black, Security

July 1, 2015 by hgpu

Spectral Ewald Acceleration of Stokesian Dynamics for polydisperse suspensions

Mu Wang, John F. Brady

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Tags: Computational Physics, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 680, Physics, Soft Condensed Matter

July 1, 2015 by hgpu

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

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Tags: Computer science, CUDA, Data mining, Deep learning, Machine learning, nVidia, Tesla K40

July 1, 2015 by hgpu

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros

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Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia, OpemMP, Package, Tesla K20

June 30, 2015 by hgpu

Intra-Application Data-Communication Characterization

Imran Ashraf, Vlad-Mihai Sima, Koen Bertels

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 640

June 30, 2015 by hgpu

CPU and GPU Implementation of QCD by using OpenCL

J. Sa, B. Noh, H. Kim, D. Choi, S. Lee, Y. Chung, D. Kim, H. Jang

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Tags: High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 550, OpenCL, Physics, QCD

June 30, 2015 by hgpu

Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs

Liang-Tsung Huang, Chao-Chin Wu, Lien-Fu Lai, Yun-Ju Li

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Tags: Bioinformatics, Biology, CUDA, Databases, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C1060, Tesla K20

June 30, 2015 by hgpu

Compiling High Performance Recursive Filters

Gaurav Chaurasia, Jonathan Ragan-Kelley, Sylvain Paris, George Drettakis, Fredo Durand

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Tags: Algorithms, CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX Titan

June 30, 2015 by hgpu

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Juergen Schmidhuber

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Tags: Computer science, CUDA, Deep learning, Image processing, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan X

June 26, 2015 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

Programming

Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

GPU phase-field lattice Boltzmann simulations of growth and motion of a binary alloy dendrite

Parallel Sparse Coding for Seafloor Image Analysis

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Spectral Ewald Acceleration of Stokesian Dynamics for polydisperse suspensions

Heterogeneous Network Embedding via Deep Architectures

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Intra-Application Data-Communication Characterization

CPU and GPU Implementation of QCD by using OpenCL

Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs

Compiling High Performance Recursive Filters

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

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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