high performance computing on graphics processing units: hgpu.org

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Scalable and High Performance Betweenness Centrality on the GPU

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, Numerical simulation, nVidia, nVidia GeForce GTX Titan, Package, Tesla M2090

August 1, 2014 by hgpu

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

D. C. Price, M. A. Clark, B. R. Barsdell, R. Babich, L. J. Greenhill

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Tags: Astrophysics, CUDA, Energy-efficient computing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 780, Package, Performance, Signal processing, Tesla K20

August 1, 2014 by hgpu

A CUDA-Based Real Parameter Optimization Benchmark

Ke Ding, Ying Tan

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 560 Ti, Optimization, Package

July 30, 2014 by hgpu

Bayesian model comparison via sequential Monte Carlo

Yan Zhou

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Tags: Algorithms, Bayesian, Mathematics, nVidia, nVidia Quadro 2000, OpenCL, Package, Statistics, Thesis

July 28, 2014 by hgpu

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Esin Yavuz, James Turner, Thomas Nowotny

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Tags: Bioinformatics, Biology, Code generation, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C2070

July 28, 2014 by hgpu

Parallel kinetic Monte Carlo simulation of Coulomb glasses

Ezequiel E. Ferrero, Alejandro B. Kolton, Matteo Palassini

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Tags: Algorithms, Condensed matter, CUDA, Disordered Systems and Neural Networks, Monte Carlo simulation, nVidia, nVidia GeForce GTX 470, Package, Tesla C2075, Tesla K20

July 24, 2014 by hgpu

Dark Sky Simulations: Early Data Release

Samuel W. Skillman, Michael S. Warren, Matthew J. Turk, Risa H. Wechsler, Daniel E. Holz, P. M. Sutter

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Package, Python, Tesla K20

July 22, 2014 by hgpu

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

Christopher Schuster

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Package, SAT

July 16, 2014 by hgpu

CUD@SAT: SAT Solving on GPUs

Alessandro Dal Pal'u, Agostino Dovier, Andrea Formisano, Enrico Pontelli

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Tags: Computer science, CUDA, Numerical simulation, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, Package, SAT, Tesla C2075

July 15, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 by hgpu

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Charalampos S. Kouzinopoulos, John-Alexander M. Assael, Themistoklis K. Pyrgiotis, Konstantinos G. Margaritis

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Tags: Algorithms, Computer science, CUDA, Databases, GPU cluster, MPI, nVidia, nVidia GeForce GT 240, Package, Tesla S1070

July 11, 2014 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Scalable and High Performance Betweenness Centrality on the GPU

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

A CUDA-Based Real Parameter Optimization Benchmark

Bayesian model comparison via sequential Monte Carlo

Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN

Parallel kinetic Monte Carlo simulation of Coulomb glasses

Dark Sky Simulations: Early Data Release

Parallel Variable Pre-Selection and Lookahead Solving on GPUs

CUD@SAT: SAT Solving on GPUs

Benchmarking the Memory Hierarchy of Modern GPUs

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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