high performance computing on graphics processing units: hgpu.org

Programming

Using multiple GPUs to accelerate string searching for digital forensic analysis

Ethan Bayne, R. Ian Ferguson, Adam T. Sampson, John Isaacs

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 970 M, nVidia GeForce GTX 980, OpenCL, String matching

November 10, 2016 by hgpu

Balancing locality and concurrency: solving sparse triangular systems on GPUs

Andrea Picciau, Gordon E. Inggs, John Wickerson, Eric C. Kerrigan, George A. Constantinides

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Tags: Algorithms, AMD FirePro W5000, ATI, Computer science, Linear Algebra, nVidia, nVidia Quadro K4000, OpenCL, Sparse matrix

November 8, 2016 by hgpu

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

Elias Stehle, Hans-Arno Jacobsen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, Sorting

November 5, 2016 by hgpu

Extensions and Limitations of the Neural GPU

Eric Price, Wojciech Zaremba, Ilya Sutskever

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, Package, Python

November 3, 2016 by hgpu

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu

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Tags: Algorithms, Computer science, Deep learning, Neural networks, NLP, nVidia, RNN, Tesla K20

November 1, 2016 by hgpu

AQsort: Scalable Multi-Array In-Place Sorting with OpenMP

Daniel Langr, Pavel Tvrdik, Ivan Simecek

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Sorting

October 29, 2016 by hgpu

Accelerating BLAS on Custom Architecture through Algorithm-Architecture Co-design

Farhad Merchant, Tarun Vatwani, Anupam Chattopadhyay, Soumyendu Raha, S K Nandy, Ranjani Narayan

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Tags: Algorithms, BLAS, Computer science, CUDA, FPGA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2050

October 29, 2016 by hgpu

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

Peter Sanders, Sebastian Lamm, Lorenz Hubschle-Schneider, Emanuel Schrade, Carsten Dachsbacher

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Mathematical Software, nVidia, nVidia GeForce GTX 980 Ti, Package

October 22, 2016 by hgpu

Energy-efficient FPGA Implementation of the k-Nearest Neighbors Algorithm Using OpenCL

Fahad Bin Muslim, Alexandros Demian, Liang Ma, Luciano Lavagno, Affaq Qamar

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Tags: Algorithms, Computer science, FPGA, Nearest neighbour, nVidia, nVidia GeForce GTX 960, nVidia Quadro K4200, OpenCL, SoC

October 22, 2016 by hgpu

Reordering strategy for blocking optimization in sparse linear solvers

Gregoire Pichon, Mathieu Faverge, Pierre Ramet, Jean Roman

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla M2070

October 15, 2016 by hgpu

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs

Kaiwei Li, Jianfei Chen, Wenguang Chen, Jun Zhu

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Tags: Algorithms, Computer science, CUDA, Information Retrieval, Latent Dirichlet allocation, Machine learning, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX Titan X

October 12, 2016 by hgpu

GPU Concurrency Choices in Graph Analytics

Masab Ahmad, Omer Khan

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX 970, OpenCL

October 8, 2016 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

Programming

Using multiple GPUs to accelerate string searching for digital forensic analysis

Balancing locality and concurrency: solving sparse triangular systems on GPUs

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

Extensions and Limitations of the Neural GPU

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

AQsort: Scalable Multi-Array In-Place Sorting with OpenMP

Accelerating BLAS on Custom Architecture through Algorithm-Architecture Co-design

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

Energy-efficient FPGA Implementation of the k-Nearest Neighbors Algorithm Using OpenCL

Reordering strategy for blocking optimization in sparse linear solvers

SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs

GPU Concurrency Choices in Graph Analytics

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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