high performance computing on graphics processing units: hgpu.org

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Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Andrew Davidson, Sean Baxter, Michael Garland, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 680, Package

February 15, 2014 by hgpu

Effective Multi-Modal Retrieval based on Stacked Auto-Encoders

Wei Wang, Beng Chin Ooi, Xiaoyan Yang, Dongxiang Zhang, Yueting Zhuang

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Tags: Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX Titan, Package, Python

February 14, 2014 by hgpu

Multi-Kepler GPU vs. Multi-Intel MIC for spin systems simulations

M. Bernaschi, M. Bisson, F. Salvadore

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Tags: Benchmarking, Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, Physics, Spin Systems, Tesla K20

February 14, 2014 by hgpu

Genetically Improved CUDA C++ Software

W. B. Langdon, M. Harman

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Tags: Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 580, nVidia Quadro NVS 290, Package, Tesla C2050, Tesla K20, Tesla T10

February 11, 2014 by hgpu

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Tim Idzenga, Evghenii Gaburov, Willem Vermin, Jan Menssen, Chris L. de Korte

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Tags: Algorithms, CUDA, Image processing, nVidia, OpenMP, Package, Tesla K20, Ultrasound

February 8, 2014 by hgpu

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

Dariusz Mrozek, Milosz Brozek, Bozena Malysiak-Mrozek

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 560 Ti, Package, Tesla C1060

February 4, 2014 by hgpu

Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

Wei Wang, Lifan Xu, John Cavazos, Howie H. Huang, Matthew Kay

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, OpenACC, OpenCL, Optimization, Package

February 4, 2014 by hgpu

A GPU accelerated algorithm for 3D Delaunay triangulation

Thanh-Tung Cao, Ashwin Nanjappa, Mingcen Gao, Tiow-Seng Tan

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Tags: Algorithms, Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Package

January 30, 2014 by hgpu

A Detailed GPU Cache Model Based on Reuse Distance Theory

Cedric Nugteren, Gert-Jan van den Braak, Henk Corporaal, Henri Bal

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, nVidia GeForce GTX 470, Package

January 29, 2014 by hgpu

Autotuning Programs with Algorithmic Choice

Jason Ansel

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Tags: Algorithms, ATI, ATI Radeon HD 6630 M, Computer science, nVidia, OpenCL, Package, Performance, Tesla C2070, Thesis

January 28, 2014 by hgpu

Optimizing Stencil Computations for NVIDIA Kepler GPUs

Naoya Maruyama, Takayuki Aoki

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Package, Tesla K20, Tesla M2075

January 26, 2014 by hgpu

clpeak – peak performance of your opencl device

Krishnaraj Bhat

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Tags: ATI, Benchmarking, Computer science, nVidia, OpenCL, Package, Performance

January 23, 2014 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

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high performance computing on graphics processing units: hgpu.org

Work-Efficient Parallel GPU Methods for Single-Source Shortest Paths

Effective Multi-Modal Retrieval based on Stacked Auto-Encoders

Multi-Kepler GPU vs. Multi-Intel MIC for spin systems simulations

Genetically Improved CUDA C++ Software

Fast 2-D Ultrasound Strain Imaging: The Benefits of Using a GPU

Parallel implementation of 3D protein structure similarity searches using a GPU and the CUDA

Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

A GPU accelerated algorithm for 3D Delaunay triangulation

A Detailed GPU Cache Model Based on Reuse Distance Theory

Autotuning Programs with Algorithmic Choice

Optimizing Stencil Computations for NVIDIA Kepler GPUs

clpeak – peak performance of your opencl device

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

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