high performance computing on graphics processing units: hgpu.org

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Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Ana Lucia Varbanescu, Merijn Verstraaten, Cees de Laat, Ate Penders, Alexandru Iosup, Henk Sips

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Tags: Algorithms, Computer science, Graph theory, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Tesla C2050

January 23, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 23, 2015 by hgpu

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Matrix multiplication, nVidia, OpenCL, Performance, Tesla K20

January 21, 2015 by hgpu

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

A Novel Implementation of QuickHull Algorithm on the GPU

Jiayin Zhang, Gang Mei, Nengxiong Xu, Kunyang Zhao

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Tags: Computational Geometry, Computer science, CUDA, Graphics, nVidia, Tesla K20

January 21, 2015 by hgpu

Opportunities for Nonvolatile Memory Systems in Extreme-Scale High Performance Computing

Jeffrey S. Vetter, Sparsh Mittal

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Tags: cpu, Energy-efficient computing, GPU, high performance computing, Memory, Storage system

January 21, 2015 by sparsh0mittal

Harnessing Aspect Oriented Programming on GPU: Application to Warp-Level Parallelism (WLP)

Jonathan Passerat-Palmbach, Pierre Schweitzer, Jonathan Caux, Pridi Siregar, Claude Mazel, David Hill

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Tags: Computer science, CUDA, nVidia, Stochastic simulation, Tesla C2050, Warp level parallelism

January 19, 2015 by hgpu

Accelerating mahout on heterogeneous clusters using HadoopCL

Xiangyu Li

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Tags: Cluster computing, Computer science, GPU cluster, Heterogeneous systems, Java, Machine learning, MapReduce, nVidia, OpenCL, Tesla K20, Thesis

January 19, 2015 by hgpu

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

Tianren Wang, Yun Jing

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Tags: CUDA, Heterogeneous systems, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C2075, Tomography

January 19, 2015 by hgpu

Hybrid Multicore Algorithms for Some Semi-Numerical Applications and Graphs

Dip Sankar Banerjee

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Tags: Algorithms, Cell processor, Computer science, CUDA, Distributed computing, List ranking, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Sorting, Thesis

January 19, 2015 by hgpu

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Michael Gowanlock, Henri Casanova

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Tags: Astrophysics, Computer science, Databases, nVidia, OpenCL, Tesla C2075

January 19, 2015 by hgpu

CURFIL: Random Forests for Image Labeling on GPU

Hannes Schulz, Benedikt Waldvogel, Rasha Sheikh, Sven Behnke

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 675 M, nVidia GeForce GTX Titan, Package, Tesla K20

January 16, 2015 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

Can Portability Improve Performance? An Empirical Study of Parallel Graph Analytics

Gunrock: A High-Performance Graph Processing Library on the GPU

Reproducible and Accurate Matrix Multiplication for GPU Accelerators

GPU concurrency: Weak behaviours and programming assumptions

A Novel Implementation of QuickHull Algorithm on the GPU

Opportunities for Nonvolatile Memory Systems in Extreme-Scale High Performance Computing

Harnessing Aspect Oriented Programming on GPU: Application to Warp-Level Parallelism (WLP)

Accelerating mahout on heterogeneous clusters using HadoopCL

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

CURFIL: Random Forests for Image Labeling on 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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