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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

An Efficient Load Balancing Method for Tree Algorithms

Osama Talaat Ibrahim, Ahmed El-Mahdy

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Tags: Algorithms, Computer science, Intel Xeon Phi, load balancing, Performance

October 3, 2017 by hgpu

OpenCL Actors – Adding Data Parallelism to Actor-based Programming with CAF

Raphael Hiesgen, Dominik Charousset, Thomas C. Schmidt

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Tags: Computer science, Data parallelism, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia GeForce GTX 780 M, OpenCL, Package, Tesla C2075

September 28, 2017 by hgpu

Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System

Taisuke Boku, Ishikawa Ken-Ichi, Yoshinobu Kuramashi, Lawrence Meadows

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Tags: Computational Physics, High Energy Physics - Lattice, Intel Xeon Phi, Mixed precision, MPI, OpenMP, Package, Physics, QCD

September 28, 2017 by hgpu

Accelerating Electron Tomography Reconstruction Algorithm ICON Using the Intel Xeon Phi Coprocessor on Tianhe-2 Supercomputer

Zihao Wang, Yu Chen, Jingrong Zhang, Lun Li, Xiaohua Wan, Zhiyong Liu, Fei Sun, Fa Zhang

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Tags: intel mic, Intel Xeon Phi, NUFFT, supercomputer, Tianhe-2

September 28, 2017 by holy

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

Dalal Sukkari, Hatem Ltaief, Mathieu Faverge, David Keyes

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Tags: Algorithms, Benchmarking, Computer science, Factorization, Intel Xeon Phi, nVidia, StarPU, Task scheduling, Tesla K80, Tesla P100

September 21, 2017 by hgpu

Accelerating Radio Astronomy with Auto-Tuning

Alessio Sclocco

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Tags: AMD FirePro W9100, AMD Radeon R9 Fury X, Astrophysics, ATI, ATI Radeon HD 6970, Intel Xeon Phi, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, OpenCL, Package, Tesla K20, Thesis

September 21, 2017 by hgpu

Out-of-core Implementation for Accelerator Kernels on Heterogeneous Clouds

Hamidreza Khaleghzadeh, Ziming Zhong, Ravi Reddy, Alexey Lastovetsky

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Tags: BLAS, Cloud, Computer science, CUBLAS, CUDA, FPGA, Heterogeneous systems, Intel Xeon Phi, Matrix multiplication, nVidia, OpenCL, Package, Virtualization

September 16, 2017 by hgpu

Optimization of the Brillouin operator on the KNL architecture

Stephan Durr

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, OpenMP, Physics, QCD

September 12, 2017 by hgpu

Optimization of Spatial Convolution in ConvNets on Intel KNL

Sangamesh Nagashattappa Ragate

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Tags: Computer science, Deep learning, Image recognition, Intel Xeon Phi, Neural networks, Thesis

September 9, 2017 by hgpu

Beyond 16GB: Out-of-Core Stencil Computations

Istvan Z. Reguly, Gihan R. Mudalige, Michael B. Giles

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Tags: Computer science, CUDA, Intel Xeon Phi, MPI, nVidia, Stencil computation, Tesla P100

September 9, 2017 by hgpu

Generating Custom Code for Efficient Query Execution on Heterogeneous Processors

Sebastian Bress, Bastian Kocher, Henning Funke, Tilmann Rabl, Volker Markl

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Tags: APU, Computer science, Databases, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Tesla K40

September 7, 2017 by hgpu

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Kernel Tuner: A search-optimizing GPU code auto-tuner

libxsmm: Library targeting Intel Architecture for specialized dense and sparse matrix operations, and deep learning primitives

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

cumf_als: CUDA Matrix Factorization Library with Alternating Least Square (ALS)

Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms

OCLADock - OpenCL Accelerated Molecular Docking

A Case Study in Using OpenCL on FPGAs: Creating an Open-Source Accelerator of the AutoDock Molecular Docking Software

sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Parallax: A Tool for Automatic Parallelization of Deep Learning Training in Distributed Multi-GPU Environments

Parallax: Automatic Data-Parallel Training of Deep Neural Networks

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image processing and Reconstruction on heterogeneous Devices

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

Spatial: Specify Parameterized Accelerators Through Inordinately Abstract Language

Spatial: A Language and Compiler for Application Accelerators

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Academic Exchange Center in Ocean University of China, Qingdao, China

The 4th International Conference on Communication and Information Processing (ICCIP), 2018

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Hida Takayama, Japan

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Nagoya University, Japan

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MediaCityUK, Salford Quays, Greater Manchester, England

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high performance computing on graphics processing units: hgpu.org

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

An Efficient Load Balancing Method for Tree Algorithms

OpenCL Actors – Adding Data Parallelism to Actor-based Programming with CAF

Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System

Accelerating Electron Tomography Reconstruction Algorithm ICON Using the Intel Xeon Phi Coprocessor on Tianhe-2 Supercomputer

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

Accelerating Radio Astronomy with Auto-Tuning

Optimization of the Brillouin operator on the KNL architecture

Optimization of Spatial Convolution in ConvNets on Intel KNL

Beyond 16GB: Out-of-Core Stencil Computations

Generating Custom Code for Efficient Query Execution on Heterogeneous Processors

Recent source codes

Kernel Tuner: A search-optimizing GPU code auto-tuner

libxsmm: Library targeting Intel Architecture for specialized dense and sparse matrix operations, and deep learning primitives

CosmoFlow: Using Deep Learning to Learn the Universe at Scale

cumf_als: CUDA Matrix Factorization Library with Alternating Least Square (ALS)

libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms

OCLADock - OpenCL Accelerated Molecular Docking

sentiment-discovery: Unsupervised Language Modeling at scale for robust sentiment classification

Parallax: A Tool for Automatic Parallelization of Deep Learning Training in Distributed Multi-GPU Environments

OpenCLIPER: an OpenCL-based C++ Framework for Overhead-Reduced Medical Image processing and Reconstruction on heterogeneous Devices

Spatial: Specify Parameterized Accelerators Through Inordinately Abstract Language

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Featured events

The 3rd International Conference on Computer Systems and Communication Technology (ICCSCT), 2018

The 4th International Conference on Communication and Information Processing (ICCIP), 2018

The Third International Workshop on GPU Computing and AI (GCA), 2018

The 5th International Conference on Power and Energy Systems Engineering (CPESE), 2018

The 10th International Conference on Information Management and Engineering (ICIME), 2018