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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

A Survey on Agent-based Simulation using Hardware Accelerators

Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, OpenCL, Overview

July 5, 2018 by hgpu

Acceleration of tensor-product operations for high-order finite element methods

Kasia Swirydowicz, Noel Chalmers, Ali Karakus, Timothy Warburton

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Tags: Computer science, CUDA, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Overview, Performance, Tesla P100

November 7, 2017 by hgpu

Introduction to the Special Issue on Digital Signal Processing in Radio Astronomy

Danny C. Price, Jonathon Kocz, Matthew Bailes, Lincoln J. Greenhill

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Tags: Astrophysics, CUDA, DSP, FPGA, nVidia, Overview, Signal processing

February 7, 2017 by hgpu

Deep Learning on FPGAs: Past, Present, and Future

Griffin Lacey, Graham W. Taylor, Shawki Areibi

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Machine learning, OpenCL, Overview

February 17, 2016 by hgpu

An Introduction to OpenCL C++

AJ Guillon

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Tags: Computer science, OpenCL, Overview, Tutorial

May 22, 2015 by hgpu

An Execution Model for OpenCL 2.0

Benedict R. Gaster

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Tags: Computer science, OpenCL, Overview

November 9, 2014 by hgpu

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Kato Mivule, Benjamin Harvey, Crystal Cobb, Hoda El Sayed

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Tags: Computer science, CUDA, MapReduce, nVidia, Overview, Pthreads, Review, Tesla K20

October 18, 2014 by hgpu

The GPUVerify Method: a Tutorial Overview

Alastair F. Donaldson

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Tags: Computer science, CUDA, nVidia, OpenCL, Overview, Package, Programming techniques, Tutorial

September 16, 2014 by hgpu

Optimization Techniques on GPU: A Survey

Rashmi Sharan Sinha, Satvir Singh

Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 285, Optimization, Overview, Particle swarm optimization, Tesla C1060, Tesla C2050

June 12, 2014 by hgpu

GPU Programming with CUDA: A brief overview

Filipo Novo Mor, Plauto de Abreu Neto

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Tags: Computer science, CUDA, nVidia, Overview

February 17, 2014 by hgpu

Computer Graphics: From Pixels to Programmable Graphics Hardware

Alexey Boreskov, Evgeniy Shikin

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Tags: 3D Graphics and Realism, Algorithms, Book, Computer science, CUDA, Games, nVidia, OpenCL, OpenGL, Overview, Real-time graphics, Rendering, Tessellation, Tutorial

November 6, 2013 by hgpu

A Computing Kernel for Network Binarization on PyTorch

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

SHA512AOCLStudy

Study of OpenCL Processing Models for FPGA Devices

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

JSDoop

JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training

FPGA CNN Acceleration

Research on OpenCL optimization for FPGA deep learning application

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

Performance Evaluation of Advanced Features in CUDA Unified Memory

Performance Evaluation of Advanced Features in CUDA Unified Memory

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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