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Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

Aditya Deshpande

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Tags: Algorithms, Compression, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 580, nVidia Quadro FX 3700, Package, Sorting, Sparse matrix, Tesla K20, Thesis

July 11, 2014 by hgpu

targetDP: an Abstraction of Lattice Based Parallelism with Portable Performance

Alan Gray, Kevin Stratford

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Tags: CUDA, Data parallelism, Fluid dynamics, Intel Xeon Phi, Lattice Boltzmann model, nVidia, Tesla K40

May 20, 2014 by hgpu

Investigating the Impact of Data Parallelism and GPU Technology on Computer Gaming

Abu Asaduzzaman, Deepthi Gummadi

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Tags: Computer science, CUDA, Data parallelism, Games, nVidia, Tesla C2075

May 17, 2014 by hgpu

A Language for Nested Data Parallel Design-space Exploration on GPUs

Bo Joel Svensson, Mary Sheeran, Ryan R. Newton

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Tags: Computer science, CUDA, Data parallelism, Haskell, nVidia, nVidia GeForce GTX 680, Tesla C2070

April 11, 2014 by hgpu

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Ashis Kumar Dash

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Quadro FX 3700

January 29, 2014 by hgpu

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Thomas Paine, Hailin Jin, Jianchao Yang, Zhe Lin, Thomas Huang

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Tags: Computer science, Computer vision, CUDA, Data parallelism, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K20

December 24, 2013 by hgpu

Heterogeneous Programming with Single Operation Multiple Data

Herve Paulino, Eduardo Marques

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Java, nVidia, nVidia GeForce GT 320 M, Tesla C2050

December 19, 2013 by hgpu

Job Parallelism using Graphical Processing Unit Individual Multi-Processors and Localised Memory

D.P. Playne, K.A. Hawick

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Tags: Computer science, CUDA, Data parallelism, nVidia, Tesla M2075

December 11, 2013 by hgpu

A Parallel Intermediate Representation for Embedded Languages

Ivar Lang

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Tags: Computer science, Data parallelism, nVidia, OpenCL, Package, Tesla M2050, Thesis

October 10, 2013 by hgpu

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Jun Liu

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Tags: Code generation, Compilers, Computer science, CUDA, Data parallelism, nVidia, Tesla C2050, Thesis

October 3, 2013 by hgpu

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

George Ungureanu

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Heterogeneous systems, Image processing, nVidia, Thesis

September 25, 2013 by hgpu

A streaming model for nested data parallelism

Frederik M. Madsen

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Tags: Algorithms, Computer science, CUDA, Data parallelism, nVidia, Thesis

September 21, 2013 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

Combining Data Parallelism and Task Parallelism for Efficient Performance on Hybrid CPU and GPU Systems

targetDP: an Abstraction of Lattice Based Parallelism with Portable Performance

Investigating the Impact of Data Parallelism and GPU Technology on Computer Gaming

A Language for Nested Data Parallel Design-space Exploration on GPUs

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

GPU Asynchronous Stochastic Gradient Descent to Speed Up Neural Network Training

Heterogeneous Programming with Single Operation Multiple Data

Job Parallelism using Graphical Processing Unit Individual Multi-Processors and Localised Memory

A Parallel Intermediate Representation for Embedded Languages

Compiler Optimizations for SIMD/GPU/Multicore Architectures

Automatic Software Synthesis from High-Level ForSyDe Models Targeting Massively Parallel Processors

A streaming model for nested data parallelism

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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