high performance computing on graphics processing units: hgpu.org

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Deep learning with COTS HPC systems

Adam Coates, Brody Huval, Tao Wang, David J. Wu, Andrew Y. Ng, Bryan Catanzaro

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Tags: Computer science, CUDA, Machine learning, MPI, Neural networks, nVidia, nVidia GeForce GTX 680

June 19, 2013 by hgpu

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

Klaus Kofler, Ivan Grasso, Biagio Cosenza, Thomas Fahringer

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Tags: ATI, ATI Radeon HD 5870, Code generation, Compilers, Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 480, OpenCL, Performance, Task scheduling

April 21, 2013 by hgpu

GPU implementation of a deep learning network for image recognition tasks

Sean Patrick Parker

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Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Thesis

March 12, 2013 by hgpu

Utilizing Graphics Processing Units for Network Anomaly Detection

Jonathan D. Hersack

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Tags: Algorithms, Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 280, Security, Thesis

February 27, 2013 by hgpu

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Shuaiwen Song, Chunyi Su, Barry Rountree, Kirk W. Cameron

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Tags: Biomolecules, Computer science, CUDA, Electrostatics, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, Tesla C2075, Tesla M2090

February 18, 2013 by hgpu

Regularization and nonlinearities for neural language models: when are they needed?

Marius Pachitariu, Maneesh Sahani

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Tags: CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 680, Statistics

January 25, 2013 by hgpu

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Dominik Grewe, Zheng Wang, Michael F.P. O'Boyle

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 580, OpenCL, Programming Languages

January 8, 2013 by hgpu

Efficient Weighted Histogramming on GPUs with CUDA

Mo Xu, Ningyi Xu, Chunshui Zhao, Feng-Hsiung Hsu

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, nVidia GeForce GTX 580

January 8, 2013 by hgpu

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Peter Richtarik, Martin Takac, Selin Damla Ahipasaoglu

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Source codes

Tags: CUBLAS, CUDA, Machine learning, nVidia, Package, Statistics

December 18, 2012 by hgpu

Scaling High Performance Domain-Specific Language Implementation with Delite

Hassan Chafi

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 275, Thesis

December 10, 2012 by hgpu

Accelerating MapReduce on a coupled CPU-GPU architecture

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: APU, ATI, ATI Radeon HD 6550, Computer science, Data mining, Heterogeneous systems, Machine learning, MapReduce, OpenCL

November 20, 2012 by hgpu

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Maria Franco, Natalio Krasnogor, Jaume Bacardit

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Tags: BioHEL, Evolutionary Computations, LCS, Learning Classifier System, Machine learning, Tesla C1060

November 1, 2012 by mariaux

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

Deep learning with COTS HPC systems

An Automatic Input-Sensitive Approach for Heterogeneous Task Partitioning

GPU implementation of a deep learning network for image recognition tasks

Utilizing Graphics Processing Units for Network Anomaly Detection

A Simplified and Accurate Model of Power-Performance Efficiency on Emergent GPU Architectures

Regularization and nonlinearities for neural language models: when are they needed?

Portable Mapping of Data Parallel Programs to OpenCL for Heterogeneous Systems

Efficient Weighted Histogramming on GPUs with CUDA

Alternating Maximization: Unifying Framework for 8 Sparse PCA Formulations and Efficient Parallel Codes

Scaling High Performance Domain-Specific Language Implementation with Delite

Accelerating MapReduce on a coupled CPU-GPU architecture

Speeding up the evaluation of evolutionary learning systems using GPGPUs

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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