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Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

Florentino Sainz, Sergi Mateo, Vicenc Beltran, Jose L. Bosque, Xavier Martorell, Eduard Ayguade

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Tags: Computer science, CUDA, Fortran, nVidia, OpenCL, Tesla M2050

December 30, 2014 by hgpu

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Saeed Taheri

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Thesis

December 30, 2014 by hgpu

Spectral classification using convolutional neural networks

Pavel Hala

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Tags: Astrophysics, Computer science, CUDA, Instrumentation and Methods for Astrophysics, Machine learning, Neural and Evolutionary Computing, nVidia, Thesis

December 30, 2014 by hgpu

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

Jonathan Passerat-Palmbach (ISIMA, UBP, LIMOS), David Hill (LIMOS, UBP, ISIMA)

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Tags: Computer science, CUDA, nVidia, Package, Pseudo-random number generators, Stochastic simulation

December 30, 2014 by hgpu

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Vajira Thambawita, Roshan Ragel, Dhammika Elkaduwe

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Performance, String matching

December 30, 2014 by hgpu

Accelerating Correlation Power Analysis Using Graphics Processing Units

Hasindu Gamaarachchi, Roshan Ragel, Darshana Jayasinghe

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, Performance, Security, Tesla C2075

December 26, 2014 by hgpu

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan

December 26, 2014 by hgpu

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Shohidul Islam, Cheol-Hong Kim, Jong-Myon Kim

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, Signal processing

December 26, 2014 by hgpu

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

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Tags: Algorithms, CNN, Computer science, CUDA, FFT, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Package, Tesla K40

December 26, 2014 by hgpu

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

Michael Edward Bauer

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Package, Tesla K20, Tesla M2090, Thesis

December 22, 2014 by hgpu

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

Lerato J. Mohapi, Simon Winberg, Michael Inggs

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Tags: Algorithms, CUDA, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Signal processing

December 22, 2014 by hgpu

Purine: A bi-graph based deep learning framework

Min Lin, Shuo Li, Xuan Luo, Shuicheng Yan

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia

December 22, 2014 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Spectral classification using convolutional neural networks

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Accelerating Correlation Power Analysis Using Graphics Processing Units

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

Purine: A bi-graph based deep learning framework

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