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ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

Nouredine Melab, The van Luong, Karima Boufaras, El-Ghazali Talbi

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 480, Package, Performance, Search

July 8, 2013 by hgpu

CrowdCL: Web-Based Volunteer Computing with WebCL

Tommy MacWilliam, Cris Cecka

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Tags: Computer science, Distributed computing, Java, nVidia, nVidia GeForce GT 320 M, OpenCL, Package, Tesla K20

July 7, 2013 by hgpu

Computing Strongly Connected Components with CUDA

Miroslav Stuhl

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

July 3, 2013 by hgpu

vSMC: Parallel Sequential Monte Carlo in C++

Yan Zhou

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Tags: Algorithms, Bayesian, Mathematical Software, Mathematics, nVidia, nVidia Quadro FX 2000, OpenCL, Package, Physics, Signal processing, Statistics

July 1, 2013 by hgpu

Intel Xeon Phi Coprocessor High-Performance Programming

Jim Jeffers, James Jeffers, James Reinders

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Tags: Book, Computer science, Intel, Intel Phi, OpenMP, Package, Review

June 30, 2013 by hgpu

Efficient computation of constrained parameterizations on parallel platforms

Theodoros Athanasiadis, Georgios Zioupos, Ioannis Fudos

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Tags: 3D Graphics and Realism, Computer science, nVidia, OpenCL, Package, Tesla C2070

June 29, 2013 by hgpu

libCudaOptimize: an Open Source Library of GPU-based Metaheuristics

Youssef S.G. Nashed, Roberto Ugolotti, Pablo Mesejo, Stefano Cagnoni

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Tags: Artificial intelligence, Computer science, CUDA, Differential evolution, Evolutionary Computations, Metaheuristics, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTS 450, Optimization, Package, Particle swarm optimization

June 21, 2013 by hgpu

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Sungin Park, Soo-Yong Shin, Kyu-Baek Hwang

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Tags: Bioinformatics, Biology, CUDA, Genetics, Multidimensional scaling, nVidia, Package

June 21, 2013 by hgpu

Delaunay Triangulation in R3 on the GPU

Ashwin Nanjappa

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 580, Package, Thesis, Voronoi diagram

June 18, 2013 by hgpu

Bayesian State-Space Modelling on High-Performance Hardware Using LibBi

Lawrence M. Murray

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Tags: Bayesian, CUDA, Mathematics, nVidia, Package, Statistics, Tesla C2075, Tesla S2050

June 17, 2013 by hgpu

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

Eric Holk, Milinda Pathirage, Arun Chauhan, Andrew Lumsdaine, Nicholas D. Matsakis

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 460, OpenCL, Package, PTX

June 17, 2013 by hgpu

Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods

Xavier Andrade, Alan Aspuru-Guzik

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Tags: ATI, ATI Radeon HD 7970, Computational Physics, Condensed matter, Data parallelism, nVidia, OpenCL, Package, Physics, Tesla K20

June 14, 2013 by hgpu

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

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high performance computing on graphics processing units: hgpu.org

Applications

ParadisEO-MO-GPU: a Framework for Parallel GPU-based Local Search Metaheuristics

CrowdCL: Web-Based Volunteer Computing with WebCL

Computing Strongly Connected Components with CUDA

vSMC: Parallel Sequential Monte Carlo in C++

Intel Xeon Phi Coprocessor High-Performance Programming

Efficient computation of constrained parameterizations on parallel platforms

libCudaOptimize: an Open Source Library of GPU-based Metaheuristics

CFMDS: CUDA-based fast multidimensional scaling for genome-scale data

Delaunay Triangulation in R3 on the GPU

Bayesian State-Space Modelling on High-Performance Hardware Using LibBi

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

Real-space density functional theory on graphical processing units: computational approach and comparison to Gaussian basis set methods

Recent source codes

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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

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