high performance computing on graphics processing units: hgpu.org

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Energy Efficient Computing on Multi-core Processors: Vectorization and Compression Techniques

Abdullah Al Hasib

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Tags: Compression, Computer science, Data parallelism, Intel Xeon Phi, Prefetch, Programming techniques, Thesis

June 20, 2018 by hgpu

Software Prefetching for Indirect Memory Accesses

Sam Ainsworth, Timothy M. Jones

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Tags: ARM, Benchmarking, Compilers, Computer science, Intel Xeon Phi, LLVM, MPI, Package, Prefetch

January 10, 2017 by hgpu

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Tarun Beri

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Tags: Computer science, CUDA, FFT, GPU cluster, Linear Algebra, Matrix multiplication, nVidia, Package, Prefetch, Tesla M2070, Thesis

November 5, 2016 by hgpu

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Andreas Klockner, Lucas C. Wilcox, T. Warburton

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Tags: Algorithms, AMD Radeon R9 Fury, ATI, Code generation, Computer science, Fortran, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, Prefetch, Programming Languages, Python, Tesla K40

April 29, 2016 by hgpu

Breadth First Search Vectorization on the Intel Xeon Phi

Mireya Paredes, Graham Riley, Mikel Lujan

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Tags: Algorithms, Computer science, Databases, Intel Xeon Phi, Prefetch

April 14, 2016 by hgpu

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Neha Agarwal, David Nellans, Mike O'Connor, Stephen W. Keckler, Thomas F. Wenisch

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Prefetch

February 6, 2015 by hgpu

Supporting Applications Involving Dynamic Data Structures and Irregular Memory Access on Emerging Parallel Platforms

Bin Ren

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Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, Memory model, nVidia, nVidia Quadro FX 5800, Prefetch, Tesla C2050, Thesis

September 19, 2014 by hgpu

Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems

Pawel Rosciszewski

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Tags: Computer science, Databases, Heterogeneous systems, nVidia, nVidia Quadro FX 3800, OpenCL, Prefetch, Tesla C2050

July 30, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Minsoo Rhu, Michael Sullivan, Jingwen Leng, Mattan Erez

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Tags: Computer science, GPGPU-sim, Memory, Performance, Prefetch

October 29, 2013 by hgpu

APOGEE: adaptive prefetching on GPUs for energy efficiency

Ankit Sethia, Ganesh Dasika, Mehrzad Samadi, Scott Mahlke

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, OpenGL, Prefetch

September 28, 2013 by hgpu

PAstudy

Double-precision FPUs in High-Performance Computing: an Embarrassment of Riches?

hpx: The C++ Standard Library for Parallelism and Concurrency

Integration of CUDA Processing within the C++ library for parallelism and concurrency (HPX)

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms, i.e., dwarfs, for state-of-art multicore CPUs, GPUs, Intel MICs and Altera FPGAs

OpenCL Performance Prediction using Architecture-Independent Features

Rodinia Benchmark Suite ported for OpenCL-capable Intel FPGAs

High Performance Computing with FPGAs and OpenCL

The Ocean Tensor Package

Tornado

Using Compiler Snippets to Exploit Parallelism on Heterogeneous Hardware: A Java Reduction Case Study

pocl: Portable Computing Language

Exploiting Task Parallelism with OpenCL: A Case Study

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

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high performance computing on graphics processing units: hgpu.org

Energy Efficient Computing on Multi-core Processors: Vectorization and Compression Techniques

Software Prefetching for Indirect Memory Accesses

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Array Program Transformation with Loo.py by Example: High-Order Finite Elements

Breadth First Search Vectorization on the Intel Xeon Phi

Unlocking Bandwidth for GPUs in CC-NUMA Systems

Supporting Applications Involving Dynamic Data Structures and Irregular Memory Access on Emerging Parallel Platforms

Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems

Performance-efficient mechanisms for managing irregularity in throughput processors

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

APOGEE: adaptive prefetching on GPUs for energy efficiency

Recent source codes

PAstudy

hpx: The C++ Standard Library for Parallelism and Concurrency

OpenDwarfs: a benchmark suite consisting of different computation/communication idioms, i.e., dwarfs, for state-of-art multicore CPUs, GPUs, Intel MICs and Altera FPGAs

Rodinia Benchmark Suite ported for OpenCL-capable Intel FPGAs

The Ocean Tensor Package

Tornado

pocl: Portable Computing Language

TVM: Open deep learning compiler stack for cpu, gpu and specialized accelerators

MyCaffe: A complete deep learning platform written almost entirely in C# for Windows developers

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks

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International Conference on Image, Video and Signal Processing (IVSP), 2019

International Joint Conference on Signals, Systems and Computers (CSSC), 2018

International Joint Conference on Robotics, Automation and Mechatronics (JCRAM), 2018

International Joint Conference on Robotics and Artificial Intelligence (JCRAI), 2018

International Joint Conference on Computer Vision and Pattern Recognition (CCVPR), 2018