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Study of Bandwidth Partitioning for Co-executing GPU Kernels

Erik Melander

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Thesis

December 7, 2017 by hgpu

A Hybrid-parallel Architecture for Applications in Bioinformatics

Jan Christian Kassens

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Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 780 Ti, Thesis

December 3, 2017 by hgpu

Methods for GPU Acceleration of Big Data Applications

Reza Mokhtari

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Tags: big data, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan Black, Thesis

December 3, 2017 by hgpu

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

Enzo Rucci, Armando De Giusti, Marcelo Naiouf

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Tags: All-Pairs Distance, Computer science, Intel Xeon Phi, OpenMP

December 3, 2017 by hgpu

STAR-RT: Visual attention for real-time video game playing

Iuliia Kotseruba, John K. Tsotsos

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Tags: AMD FirePro W7000, Artificial intelligence, ATI, Computer science, Games, GLSL, OpenCL, OpenGL

December 3, 2017 by hgpu

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Qualcomm Technologies, Inc

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Tags: Computer science, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Implementing implicit OpenMP data sharing on GPUs

Gheorghe-Teodor Bercea, Carlo Bertolli, Arpith C. Jacob, Alexandre Eichenberger, Alexey Bataev, Georgios Rokos, Hyojin Sung, Tong Chen, Kevin O'Brien

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Tags: Computer science, CUDA, LLVM, Memory model, nVidia, OpenMP, Programming Languages, PTX, Tesla K40, Tesla P100

November 30, 2017 by hgpu

2D Image Convolution using Three Parallel Programming Models on the Xeon Phi

Ashkan Tousimojarad, Wim Vanderbauwhede, W Paul Cockshott

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenCL, OpenMP, Programming Languages

November 30, 2017 by hgpu

fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs

Stylianos I. Venieris, Christos-Savvas Bouganis

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Neural networks

November 30, 2017 by hgpu

Intel FPGA SDK for OpenCL

Intel Corporation

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Tags: Computer science, FPGA, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Shaohuai Shi, Xiaowen Chu

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Tags: Algorithms, Benchmarking, Caffe, Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Package, Performance, TensorFlow, Tesla P40, Torch

November 26, 2017 by hgpu

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

Maxence Reberol, Bruno Levy

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Tags: Computer science, nVidia, nVidia GeForce GTX 1080, OpenGL, Package, Traingular meshes

November 26, 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

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high performance computing on graphics processing units: hgpu.org

Applications

Study of Bandwidth Partitioning for Co-executing GPU Kernels

A Hybrid-parallel Architecture for Applications in Bioinformatics

Methods for GPU Acceleration of Big Data Applications

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

STAR-RT: Visual attention for real-time video game playing

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Implementing implicit OpenMP data sharing on GPUs

2D Image Convolution using Three Parallel Programming Models on the Xeon Phi

fpgaConvNet: A Toolflow for Mapping Diverse Convolutional Neural Networks on Embedded FPGAs

Intel FPGA SDK for OpenCL

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Computing the distance between two finite element solutions defined on different 3D meshes on a GPU

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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