high performance computing on graphics processing units: hgpu.org

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Design and Performance Analysis of Parallel Processing of SRTP Packets

Jan Wozniak

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Tags: Computer science, Intel, OpenCL, Security

April 26, 2013 by hgpu

Accelerating Population Balance Model-based particulate process simulations via parallel computing

Anuj Varghese Prakash

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Tags: Biochemistry, Chemistry, Computer science, CUDA, Distributed computing, nVidia, nVidia GeForce GTX 280, Thesis

April 26, 2013 by hgpu

High Performance Computing with GPUs

Nikita Vakulin, Riley Shaw, Timothy Livingston

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Tags: Computer science, CUDA, Differential equations, Finite element method, nVidia, Package

April 25, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Faster Upper Body Pose Estimation and Recognition Using CUDA

Dane L. Brown, Mehrdad Ghaziasgar, James Connan

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 580

April 25, 2013 by hgpu

Reduce, Reuse, Recycle (R^3): a Design Methodology for Sparse Matrix Vector Multiplication on Reconfigurable Platforms

Kevin Townsend, Joseph Zambreno

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla M2090, Tesla S1070

April 23, 2013 by hgpu

Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

CYN Dwith, Rathna.G.N

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Tags: Algorithms, ATI, Computer science, Heterogeneous systems, OpenCL, Pattern recognition

April 23, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

GPU Scripting and Code Generation with PyCUDA

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

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

SW# – GPU enabled exact alignments on genome scale

Matija Korpar, Mile Sikic

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 570, nVidia GeForce GTX 690, Package, Sequence alignment, Smith-Waterman algorithm

April 23, 2013 by hgpu

GPU-based Implementation of 128-bit Secure Eta Pairing Over a Binary Field

Utsab Bose, Anup Kumar Bhattacharya, Abhijit Das

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Tags: Algorithms, Computer science, CUDA, Elliptic curves, nVidia, nVidia GeForce GTX 480, Security, Tesla C2050

April 22, 2013 by hgpu

Automatic Parallelization of a Gap Model using Java and OpenCL

Jonathan Passerat-Palmbach, Arthur Forest, Julien Pal, Bruno Corbara, D.R.C. Hill

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Tags: Computer science, Java, nVidia, nVidia GeForce GTX 590, OpenCL, Tesla C1060, Tesla C2050

April 22, 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

Design and Performance Analysis of Parallel Processing of SRTP Packets

Accelerating Population Balance Model-based particulate process simulations via parallel computing

High Performance Computing with GPUs

Directive-based Approach to Heterogeneous Computing

Faster Upper Body Pose Estimation and Recognition Using CUDA

Reduce, Reuse, Recycle (R^3): a Design Methodology for Sparse Matrix Vector Multiplication on Reconfigurable Platforms

Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

Solving Wave Equations on Unstructured Geometries

GPU Scripting and Code Generation with PyCUDA

SW# – GPU enabled exact alignments on genome scale

GPU-based Implementation of 128-bit Secure Eta Pairing Over a Binary Field

Automatic Parallelization of a Gap Model using Java and OpenCL

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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