high performance computing on graphics processing units: hgpu.org

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Power analysis of sorting algorithms on FPGA using OpenCL

Aidan O Mahony, Emanuel Popovici

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Tags: Computer science, Energy-efficient computing, FPGA, OpenCL, Performance, Sorting

November 3, 2018 by hgpu

Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs

Francisco M. Castro, Nicolas Guil, Manuel J. Marin-Jimenez, Jesus Perez-Serrano, Manuel Ujaldon

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Tags: Artificial intelligence, CNN, Computer science, Computer vision, CUDA, Deep learning, Energy-efficient computing, Neural networks, nVidia, nVidia GeForce GTX Titan X

August 5, 2018 by hgpu

Energy efficiency of finite difference algorithms on multicore CPUs, GPUs, and Intel Xeon Phi processors

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Finite difference, Intel Xeon Phi, nVidia, Tesla K40

October 3, 2017 by hgpu

Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

Jesus Perez Serrano, Edans Flavius De Oliveira Sandes, Alba Cristina Magalhaes Alves de Melo, Manuel Ujaldon

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Tags: Bioinformatics, Biology, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 980, Performance, Smith-Waterman algorithm

June 10, 2017 by hgpu

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Mohammed A. Noaman Al-hayanni, Rishad Shafik, Ashur Rafiev, Fei Xia, Alex Yakovlev

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

June 5, 2017 by hgpu

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Ben Taylor, Vicent Sanz Marco, Zheng Wang

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Tags: ARM, Computer science, Energy-efficient computing, Heterogeneous systems, Machine learning, OpenCL

April 30, 2017 by hgpu

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

Suejb Memeti, Lu Li, Sabri Pllana, Joanna Kolodziej, Christoph Kessler

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP, Performance

April 20, 2017 by hgpu

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Maria Barreda Vaya

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OmpSs, Tesla C2050, Thesis

April 11, 2017 by hgpu

Achieving high-performance with a sparse direct solver on Intel KNL

Emmanuel Agullo, Alfredo Buttari, Mikko Byckling, Abdou Guermouche, Ian Masliah

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Sparse direct solvers

March 9, 2017 by hgpu

A 7.663-TOPS 8.2-W Energy-efficient FPGA Accelerator for Binary Convolutional Neural Networks

Yixing Li, Zichuan Liu, Kai Xu, Hao Yu, Fengbo Ren

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Tags: CNN, Computer science, CUDA, Deep learning, Energy-efficient computing, FPGA, Hardware Architecture, Neural networks, nVidia, nVidia GeForce GTX Titan X, Performance

February 22, 2017 by hgpu

An initial performance review of software components for a heterogeneous computing platform

Ivan Svogor

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Tags: ATI, ATI Radeon HD 7750, Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, OpenCL, Performance, Robotics

January 4, 2017 by hgpu

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Yun Wu, Dimitrios S. Nikolopoulos, Roger Woods

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Tags: ARM, Benchmarking, Computer science, Energy-efficient computing, FPGA, Heterogeneous systems, OpenCL, OpenMP, SoC

September 20, 2016 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

Power analysis of sorting algorithms on FPGA using OpenCL

Energy-based Tuning of Convolutional Neural Networks on Multi-GPUs

Energy efficiency of finite difference algorithms on multicore CPUs, GPUs, and Intel Xeon Phi processors

Smith-Waterman Acceleration in Multi-GPUs: A Performance per Watt Analysis

Speedup and Parallelization Models for Energy-Efficient Many-Core Systems Using Performance Counters

Adaptive Optimization for OpenCL Programs on Embedded Heterogeneous Systems

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

Performance and energy optimization of the iterative solution of sparse linear systems on multicore processors

Achieving high-performance with a sparse direct solver on Intel KNL

A 7.663-TOPS 8.2-W Energy-efficient FPGA Accelerator for Binary Convolutional Neural Networks

An initial performance review of software components for a heterogeneous computing platform

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

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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