high performance computing on graphics processing units: hgpu.org

Emanouil Atanassov, Michaela Barth, Mikko Byckling, Vali Codreanu, Nevena Ilieva, Tomas Karasek, Jorge Rodriguez, Sami Saarinen, Ole Widar Saastad, Michael Schliephake, Martin Stachon, Janko Strassburg, Volker Weinberg (Editor)

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Tags: Benchmarking, Computer science, Intel Xeon Phi, OpenMP, Performance

February 14, 2017 by hgpu

cellGPU: massively parallel simulations of dynamic vertex models

Daniel M. Sussman

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Tags: Biological Physics, CUDA, nVidia, Package, Physics, Tesla K40

February 14, 2017 by hgpu

Improved Lossless Image Compression Model Using Coefficient Based Discrete Wavelet Transform

T. Velumani, S. Sukumaran

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Tags: Compression, Computational Complexity, Discrete Wavelet Transform, Image processing, OpenCL, Probability

February 14, 2017 by hgpu

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit Mishra, Ganesh Venkatesh, Debbie Marr

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Tags: Algorithms, ASIC, Computer science, CUDA, Deep learning, FPGA, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1, Performance

February 14, 2017 by hgpu

Development of JavaScript-based deep learning platform and application to distributed training

Masatoshi Hidaka, Ken Miura, Tatsuya Harada

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Tags: Computer science, Deep learning, Java, Neural networks, nVidia, OpenCL, Package, Tesla K80, WebCL

February 10, 2017 by hgpu

GPU-Accelerated SVM Training Algorithm Based on PC and Mobile Device

Yi-Yan Nan, Quan-Zhe Li, Jin-Chun Piao, Shin-Dug Kim

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Tags: Algorithms, AMD Radeon R9 M200X, Android, ATI, Computer science, Image processing, Matrix multiplication, OpenCL, Pattern recognition

February 10, 2017 by hgpu

gearshifft – The FFT Benchmark Suite for Heterogeneous Platforms

Peter Steinbach, Matthias Werner

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Tags: Algorithms, Benchmarking, Computer science, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, Tesla K20, Tesla K80, Tesla P100

February 10, 2017 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

LAMMPS’ PPPM Long-Range Solver for the Second Generation Xeon Phi

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Trie Compression for GPU Accelerated Multi-Pattern Matching

MapSQ: A MapReduce-based Framework for SPARQL Queries on GPU

Improving the Performance of Fully Connected Neural Networks by Out-of-Place Matrix Transpose

Best Practice Guide Intel Xeon Phi v2.0

cellGPU: massively parallel simulations of dynamic vertex models

Improved Lossless Image Compression Model Using Coefficient Based Discrete Wavelet Transform

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC

Development of JavaScript-based deep learning platform and application to distributed training

GPU-Accelerated SVM Training Algorithm Based on PC and Mobile Device

gearshifft – The FFT Benchmark Suite for Heterogeneous Platforms

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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