high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

Using OpenCL to Calculate a Pressure Field

David Prairie, Cory Klokman, Leo Makowski

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Tags: Computer science, CUDA, nVidia, OpenCL

May 29, 2012 by hgpu

Massively Parallel Neural Encoding and Decoding of Visual Stimuli

Aurel A. Lazar, Yiyin Zhou

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Neural networks, nVidia, Tesla M2050

May 29, 2012 by hgpu

Explicit Cache Management for Volume Ray-Casting on Parallel Architectures

Daniel Jonsson, Per Ganestam, Anders Ynnerman, Michael Doggett, Timo Ropinski

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 570, OpenCL, Package, Rendering

May 29, 2012 by hgpu

Parameterized Verification of GPU Kernel Programs

Guodong Li, Ganesh Gopalakrishnan

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Tags: Computer science, CUDA, nVidia, Optimization

May 26, 2012 by hgpu

Parallel Parametric Optimisation with Firefly Algorithms on Graphical Processing Units

A.V. Husselmann, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Optimization

May 26, 2012 by hgpu

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Richelle Ann B. Juayong, Francis George C. Cabarle, Henry N. Adorna, Miguel A. Martinez-del-Amor

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Tags: Computer science, CUDA, Membrane computing, nVidia, P systems

May 25, 2012 by hgpu

Effective Sparse Matrix Representation for the GPU Architectures

B. Neelima, Prakash S. Raghavendra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, Optimization, Sparse matrix

May 25, 2012 by hgpu

Accelerating In-Memory Graph Database traversal using GPGPUS

Ashwin Raghav Mohan Ganesh

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

May 25, 2012 by hgpu

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Rohit Sinha, Aayush Prakash, Hiren D. Patel

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Tags: Computer science, CUDA, nVidia, Tesla C2075

May 25, 2012 by hgpu

Java on CUDA architecture

Jan Strnad

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Tags: Computer science, CUDA, Image processing, Java, Linear Algebra, Matrix multiplication, nVidia, Thesis

May 24, 2012 by hgpu

Sparse direct solvers with accelerators over DAG runtimes

Xavier Lacoste, Pierre Ramet, Mathieu Faverge, Yamazaki Ichitaro, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla T20

May 24, 2012 by hgpu

Tuning a Finite Difference Computation for Parallel Vector Processors

Gerhard Zumbusch

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Tags: Algorithms, Computer science, Finite difference, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, nVidia GeForce GTX 680, OpenCL, Performance

May 24, 2012 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

Using OpenCL to Calculate a Pressure Field

Massively Parallel Neural Encoding and Decoding of Visual Stimuli

Explicit Cache Management for Volume Ray-Casting on Parallel Architectures

Parameterized Verification of GPU Kernel Programs

Parallel Parametric Optimisation with Firefly Algorithms on Graphical Processing Units

On the Simulations of Evolution-Communication P Systems with Energy without Antiport Rules for GPUs

Effective Sparse Matrix Representation for the GPU Architectures

Accelerating In-Memory Graph Database traversal using GPGPUS

Parallel simulation of mixed-abstraction SystemC models on GPUs and multicore CPUs

Java on CUDA architecture

Sparse direct solvers with accelerators over DAG runtimes

Tuning a Finite Difference Computation for Parallel Vector Processors

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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