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GPU Computing to Improve Game Engine Performance

Abu Asaduzzaman, Hin Y. Lee

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Tags: Computer science, CUDA, Data parallelism, Games, Image processing, nVidia, nVidia GeForce 8800 GTX, Performance

July 28, 2014 by hgpu

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

S. V. Ghorpade, S. M. Kamalapur

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Metaheuristics, nVidia, nVidia GeForce GTX 680, Search

July 23, 2014 by hgpu

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX Titan

July 20, 2014 by hgpu

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

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

GPU Computing to Improve Game Engine Performance

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

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

Recent source codes

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

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