high performance computing on graphics processing units: hgpu.org

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GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

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Tags: Computer science, Computer vision, CUDA, Data parallelism, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K20

December 24, 2013 by hgpu

Large-Scale Paralleled Sparse Principal Component Analysis

W. Liu, H. Zhang, D. Tao, Y. Wang, K. Lu

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Numerical Analysis, nVidia, Tesla C2050

December 24, 2013 by hgpu

GPU Acceleration of Melody Accurate Matching in Query-by-Humming

Liming Xiao, Yao Zheng, Wenqi Tang, Guangchao Yao, Li Ruan

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480

December 23, 2013 by hgpu

Enabling High Performance Computing in Cloud Infrastructure using Virtualized GPUs

Andrew J. Younge, John Paul Walters, Steve Crago, Geoffrey C. Fox

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Tags: Cloud, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20, Virtualization

December 23, 2013 by hgpu

Hardware Acceleration Technologies in Computer Algebra: Challenges and Impact

Sardar Anisul Haque

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Sorting, Sparse matrix, Tesla C2050, Tesla M2050, Thesis

December 23, 2013 by hgpu

Fast Training of Convolutional Networks through FFTs

Michael Mathieu, Mikael Henaff, Yann LeCun

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Tags: Algorithms, Computer science, Computer vision, CUDA, FFT, Machine learning, nVidia

December 23, 2013 by hgpu

Resource Centered Computing delivering high parallel performance

Jens Gustedt, Stephane Vialle, Patrick Mercier

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Tags: Computer science, CUBLAS, CUDA, GPU cluster, Hierarchical clustering, MPI, nVidia, nVidia GeForce GTX 580

December 22, 2013 by hgpu

Speed-Up Improvement Using Parallel Approach in Image Steganography

JyothiUpadhya K, U Dinesh Acharya, Hemalatha S

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Tags: Algorithms, Image processing, nVidia, nVidia GeForce GT 640, OpenCL

December 22, 2013 by hgpu

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

H. Khaled, R. El Gohary, N. L. Badr, H. M. Faheem

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 540 M, Sequence alignment, Smith-Waterman algorithm

December 22, 2013 by hgpu

Architecting an LTE Base Station with Graphics Processing Units

Q. Zheng, Y. Chen, R. Dreslinski, C. Chakrabarti, A. Anastasopoulos, S. Mahlke, T. Mudge

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Wireless baseband architecture

December 21, 2013 by hgpu

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Adrian Ratter, Claude Sammut, Matthew McGill

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 570

December 21, 2013 by hgpu

Parallel Compact Genetic Algorithm on CUDA-C Platform

Vuppuluri Sumati

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Genetic programming, nVidia

December 21, 2013 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Large-Scale Paralleled Sparse Principal Component Analysis

GPU Acceleration of Melody Accurate Matching in Query-by-Humming

Hardware Acceleration Technologies in Computer Algebra: Challenges and Impact

Fast Training of Convolutional Networks through FFTs

Resource Centered Computing delivering high parallel performance

Speed-Up Improvement Using Parallel Approach in Image Steganography

Accelerating Pairwise DNA Sequence Alignment using the CUDA Compatible GPU

Architecting an LTE Base Station with Graphics Processing Units

GPU Accelerated Graph SLAM and Occupancy Voxel Based ICP For Encoder-Free Mobile Robots

Parallel Compact Genetic Algorithm on CUDA-C Platform

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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