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FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10

Ke He, Bo Liu, Yu Zhang, Andrew Ling, Dian Gu

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Tags: Caffe, Computer science, Deep learning, FPGA, Neural networks, OpenCL

November 24, 2019 by hgpu

A Highly Parameterizable Framework for Conditional Restricted Boltzmann Machine Based Workloads Accelerated With FPGAs and OpenCL

Zoran Jaksic, Nicola Cadenelli, David Buchaca Prats, Jorda Polo, Josep Lluis Berral Garcia, David Carrera Perez

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Tags: Computer science, FPGA, HLS, Linear Algebra, Matrix multiplication, Neural networks, OpenCL

November 17, 2019 by hgpu

Framework for Parallel Kernels Auto-tuning

Filip Petrovič

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Tags: Auto-Tuning, Computer science, CUDA, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce GTX 970, OpenCL, Package, Performance, Thesis

November 10, 2019 by hgpu

CL-VIS: Visualization Platform for Understanding and Checking the OpenCL Programs

SeongKi Kim, HyukSoo Han

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Tags: Computer science, nVidia, nVidia GeForce GTX 960 M, OpenCL, Visualization

November 10, 2019 by hgpu

Study of OpenCL Processing Models for FPGA Devices

Piotr Szkotak, Pawel Russek, Kazimierz Wiatr

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Tags: Computer science, FPGA, OpenCL, Package, Security

November 10, 2019 by hgpu

Accelerating Stochastic Simulations on GPUs Using OpenCL

Pilsung Kang

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Tags: Heterogeneous systems, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Physics, Stochastic simulation

November 10, 2019 by hgpu

In-memory database acceleration on FPGAs: a survey

Jian Fang, Yvo T. B. Mulder, Jan Hidders, Jinho Lee, H. Peter Hofstee

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Tags: Computer science, Databases, FPGA, HLS, OpenCL, survey

November 3, 2019 by hgpu

Implementing and evaluating an heterogeneous, scalable, tridiagonal linear system solver with OpenCL to target FPGAs, GPUs, and CPUs

Hamish J. Macintosh, Jasmine E. Banks, Neil A. Kelson

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Tags: Computer science, FPGA, Linear Algebra, nVidia, nVidia Quadro M 4000, OpenCL

November 3, 2019 by hgpu

Research on OpenCL optimization for FPGA deep learning application

Shuo Zhang, Yanxia Wu, Chaoguang Men, Hongtao He, Kai Liang

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Tags: Computer science, Deep learning, FPGA, OpenCL, Package

November 3, 2019 by hgpu

A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit

Filip Petrovič, David Střelák, Jana Hozzová, Jaroslav Oľha, Richard Trembecký, Siegfried Benkner, Jiří Filipovič

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Tags: AMD Radeon RX Vega 56, Auto-Tuning, Benchmarking, Computer science, CUDA, Electron microscopy, Intel Xeon Phi, Microscopy, nVidia, nVidia GeForce GTX 1070, nVidia GeForce GTX 750, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance, performance portability, Tesla K20

October 27, 2019 by hgpu

AI Benchmark: All About Deep Learning on Smartphones in 2019

Andrey Ignatov, Radu Timofte, Andrei Kulik, Seungsoo Yang, Ke Wang, Felix Baum, Max Wu, Lirong Xu, Luc Van Gool

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Tags: Android, Benchmarking, Computer science, CUDA, Deep learning, nVidia, OpenCL, Overview

October 20, 2019 by hgpu

The Memory Controller Wall: Benchmarking the Intel FPGA SDK for OpenCL Memory Interface

Hamid Reza Zohouri, Satoshi Matsuoka

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Tags: Benchmarking, Computer science, FPGA, HLS, Memory, nVidia, OpenCL, Package, Tesla K20, Tesla V100

October 20, 2019 by hgpu

HPCToolkit

Refining HPCToolkit for application performance analysis at exascale

Open Catalog of Best Practices for Modernization and Optimization

Optimizing the Weather Research and Forecasting Model with OpenMP Offload and Codee

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

Exploring Scalability in C++ Parallel STL Implementations

GPU-Smash: Compression abstraction library

A Parallel Compression Pipeline for Improving GPU Virtualization Data Transfers

Noarr Structures

Abstractions for C++ code optimizations in parallel high-performance applications

$3D-fractal-generators$

HiCCL: A hierarchical collective communications library with portable optimizations

HiCCL: A Hierarchical Collective Communication Library

See all packages

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high performance computing on graphics processing units: hgpu.org

FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10

A Highly Parameterizable Framework for Conditional Restricted Boltzmann Machine Based Workloads Accelerated With FPGAs and OpenCL

Framework for Parallel Kernels Auto-tuning

CL-VIS: Visualization Platform for Understanding and Checking the OpenCL Programs

Study of OpenCL Processing Models for FPGA Devices

Accelerating Stochastic Simulations on GPUs Using OpenCL

In-memory database acceleration on FPGAs: a survey

Implementing and evaluating an heterogeneous, scalable, tridiagonal linear system solver with OpenCL to target FPGAs, GPUs, and CPUs

Research on OpenCL optimization for FPGA deep learning application

A Benchmark Set of Highly-efficient CUDA and OpenCL Kernels and its Dynamic Autotuning with Kernel Tuning Toolkit

AI Benchmark: All About Deep Learning on Smartphones in 2019

The Memory Controller Wall: Benchmarking the Intel FPGA SDK for OpenCL Memory Interface

Recent source codes

HPCToolkit

Open Catalog of Best Practices for Modernization and Optimization

Owl: Differential-based Side-Channel Leakage Detection for CUDA Applications

pSTL-Bench: Micro-benchmark suite designed to evaluate the scalability and efficiency of parallel C++ STL implementations

GPU-Smash: Compression abstraction library

Noarr Structures

3D-fractal-generators

SyncPerformance

VerCors: a verification toolset for verifying parallel and concurrent software

HiCCL: A hierarchical collective communications library with portable optimizations

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