high performance computing on graphics processing units: hgpu.org

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WPA/WPA2 Password Security Testing using Graphics Processing Units

Sorin Andrei Visan

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GT 610 M, Security

February 23, 2014 by hgpu

Parallel Spectral Graph Partitioning on CUDA

Orhan Firat, Alptekin Temizel

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Tags: Algorithms, CUDA, Image processing, Machine learning, nVidia, Tesla C2070

February 23, 2014 by hgpu

Fast Boolean Calculations Using the GPU

Bernd Steinbach, Matthias Werner

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Tags: Computer science, CUDA, nVidia, Tesla C2070

February 21, 2014 by hgpu

Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Gang Mei, Hong Tian

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

February 21, 2014 by hgpu

Computing least squares condition numbers on hybrid multicore/GPU systems

Marc Baboulin, Jack Dongarra, Remi Lacroix

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Tesla C2075

February 21, 2014 by hgpu

MICA: A fast short-read aligner that takes full advantage of Intel Many Integrated Core Architecture (MIC)

Sze-Hang Chan, Jeanno Cheung, Edward Wu, Heng Wang, Chi-Man Liu, Xiaoqian Zhu, Shaoliang Peng, Ruibang Luo, Tak-Wah Lam

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Tags: Bioinformatics, Biology, Intel Xeon Phi, Package

February 21, 2014 by hgpu

Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

Jae-Hyeon Parq, Erik Sevre, Sang-Mook Lee

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Tags: Computer science, CUDA, MPI, nVidia, nVidia Quadro 4000

February 21, 2014 by hgpu

X-ray CT on the GPU

Ravikiran Tadepalli

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Tags: Algorithms, CUDA, Medicine, nVidia, Tesla C1060, Thesis, Tomography

February 19, 2014 by hgpu

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Jianting Zhang, Simin You

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, nVidia Quadro 6000, Tesla C2050

February 19, 2014 by hgpu

Using of GPUs for cluster analysis of large data by K-means method

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

Parallel algorithms for problems of cluster analysis with very large amount of data

Natalya Litvinenko

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Tags: Algorithms, Cluster analysis, Computer science, CUDA, Nearest neighbour, nVidia, nVidia GeForce GTX 660

February 19, 2014 by hgpu

Fast Hamiltonian Monte Carlo Using GPU Computing

Andrew L. Beam, Sujit K. Ghosh, Jon Doyle

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Tags: Algorithms, Bayesian, CUDA, CULA, Monte Carlo simulation, nVidia, Package, Python, Statistics, Tesla K20

February 19, 2014 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

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

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

WPA/WPA2 Password Security Testing using Graphics Processing Units

Parallel Spectral Graph Partitioning on CUDA

Fast Boolean Calculations Using the GPU

Performance Impact of Data Layout on the GPU-accelerated IDW Interpolation

Computing least squares condition numbers on hybrid multicore/GPU systems

MICA: A fast short-read aligner that takes full advantage of Intel Many Integrated Core Architecture (MIC)

Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation

X-ray CT on the GPU

Large-Scale Geospatial Processing on Multi-Core and Many-Core Processors: Evaluations on CPUs, GPUs and MICs

Using of GPUs for cluster analysis of large data by K-means method

Parallel algorithms for problems of cluster analysis with very large amount of data

Fast Hamiltonian Monte Carlo Using GPU Computing

Recent source codes

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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