high performance computing on graphics processing units: hgpu.org

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hgpu.org » Programming » Algorithms

Fractal Art Generation using GPUs

Will.D. Mayfield, Justin.C. Eiland, Taylor.J. Hutyra, Matt.C. Paulsen, Bryant.M. Wyatt

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Tags: Algorithms, Computer science, CUDA, Graphics, Image generation, nVidia, nVidia GeForce GTX Titan

November 13, 2016 by hgpu

Shuffle Reduction Based Sparse Matrix-Vector Multiplication on Kepler GPU

Yuan Tao, Huang Zhi-Bin

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla K20

November 10, 2016 by hgpu

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

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

Programming

Fractal Art Generation using GPUs

Shuffle Reduction Based Sparse Matrix-Vector Multiplication on Kepler GPU

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

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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