high performance computing on graphics processing units: hgpu.org

Applications

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An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Nam-Luc Tran, Sabri Skhiri, Arnaud Schils, Edgar Isaac Hiroshi Leon Saiki

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan, Package

December 2, 2014 by hgpu

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

Naresh Balaji, Esin Yavuz, Thomas Nowotny

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Tags: Algorithms, Code generation, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GT 755 M, Package

December 2, 2014 by hgpu

GPU accelerated feature algorithms for mobile devices

Seth Hall

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Tags: Algorithms, Augmented reality, Clustering, Computer science, Computer vision, OpenCV, OpenGL, Thesis

December 2, 2014 by hgpu

An Open-Source GPU-Accelerated Feature Extraction Tool

Josef Michalek, Jan Vanek

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 660, OpenCL, Speech recognition

December 1, 2014 by hgpu

GPU Declarative Framework

Robert W. Senser, Jr.

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Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Chih-Sheng Lin

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, OpenCL, Task scheduling, Tesla C2050, Thesis

December 1, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 by hgpu

pyMIC: A Python Offload Module for the Intel Xeon Phi Coprocessor

Michael Klemm, Jussi Enkovaara

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Tags: Computer science, Intel Xeon Phi, Python

December 1, 2014 by hgpu

A Framework for Composing High-Performance OpenCL from Python Descriptions

Michael Anderson

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce GTX 480, OpenCL, Optical flow, Python, Thesis

November 29, 2014 by hgpu

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

Guray Ozen

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Tesla M2090, Thesis

November 29, 2014 by hgpu

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Everett Phillips, Massimiliano Fatica

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential equations, nVidia, Partial differential equations, PDEs, Tesla K20

November 29, 2014 by hgpu

Runtime Comparison of CPU and GPU Using Portable Programming Models

Franz Wiesinger, Florian Nairz, Michael Bogner

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 680, OpenCL, Sorting

November 29, 2014 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

An Approach for Maximizing Performance on Heterogeneous Clusters of CPU and GPU

Scalability and Optimization Strategies for GPU Enhanced Neural Networks (GeNN)

GPU accelerated feature algorithms for mobile devices

An Open-Source GPU-Accelerated Feature Extraction Tool

GPU Declarative Framework

Application Synthesis and Optimization on Heterogeneous Parallel Processing Systems

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

pyMIC: A Python Offload Module for the Intel Xeon Phi Coprocessor

A Framework for Composing High-Performance OpenCL from Python Descriptions

Code Generation Compiler for the OpenMP 4.0 Accelerator Model onto OMPSS

A CUDA implementation of the High Performance Conjugate Gradient benchmark

Runtime Comparison of CPU and GPU Using Portable Programming Models

Recent source codes

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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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