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Loop Perforation in OpenACC

Ahmad Lashgar, Ehsan Atoofian, Amirali Baniasadi

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Tags: Computer science, CUDA, OpenACC, OpenCL, Package, Performance

April 20, 2019 by hgpu

On Optimizing Complex Stencils on GPUs

Prashant Singh Rawat, Miheer Vaidya, Aravind Sukumaran-Rajam, Atanas Rountev, Louis-Noël Pouchet, P. Sadayappan

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Tags: Code generation, Computer science, CUDA, nVidia, Stencil computation, Tesla P100

April 20, 2019 by hgpu

Real world applications of Artificial Intelligence on constrained hardware

Wiebe Van Ranst

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Tags: Artificial intelligence, Computer science, Computer vision, Image processing, nVidia, nVidia Jetson TX2, OpenCL, Thesis

April 20, 2019 by hgpu

Concurrent query processing in a GPU-based database system

Hao Li, Yi-Cheng Tu, Bo Zeng

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan X, Package

April 20, 2019 by hgpu

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

Rod Burns, John Lawson, Duncan McBain, Daniel Soutar

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Tags: Computer science, Computer vision, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, SYCL

April 14, 2019 by hgpu

Distributed Deep Learning Strategies For Automatic Speech Recognition

Wei Zhang, Xiaodong Cui, Ulrich Finkler, Brian Kingsbury, George Saon, David Kung, Michael Picheny

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Tags: Computer science, CUDA, Deep learning, LSTM, Machine learning, nVidia, OpenMPI, Speech recognition, Tesla P100

April 14, 2019 by hgpu

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

Harri Renney, Benedict R. Gaster, Tom Mitchell

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Tags: AMD Radeon 530, ATI, FDTD, Finite-difference time-domain, OpenCL, OpenGL, Package, Physics

April 14, 2019 by hgpu

On the Representation of Partially Specified Implementations and its Application to the Optimization of Linear Algebra Kernels on GPU

Ulysse Beaugnon, Basile Clément, Nicolas Tollenaere, Albert Cohen

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Tags: Analytical model, Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro K4000, Programming Languages

April 14, 2019 by hgpu

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

John Lawson, Mehdi Goli, Duncan McBain, Daniel Soutar, Louis Sugy

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Tags: AMD R9 Nano, ATI, BLAS, Computer science, Deep learning, Linear Algebra, Machine learning, Mathematical Software, OpenCL, Package, Performance, performance portability, SYCL

April 14, 2019 by hgpu

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

Kun Yang, Yi-Fan Chen, Georgios Roumpos, Chris Colby, John Anderson

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Tags: Cloud, CUDA, Ising model, Machine learning, Monte Carlo simulation, Neural networks, nVidia, Package, Physics, Tesla V100, TPU

April 7, 2019 by hgpu

The Study of the OpenCL Processing Models for the FPGA Devices

Piotr Szkotak, Pawel Russek, Kazimierz Wiatr

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Tags: AMD Radeon R9 290, ATI, Computer science, FPGA, HLS, nVidia, nVidia GeForce GTX 1080, OpenCL, Package

April 7, 2019 by hgpu

Full-System Simulation of Mobile CPU/GPU Platforms

Kuba Kaszyk, Harry Wagstaff, Tom Spink, Bjorn Franke, Mike O'Boyle, Bruno Bodin

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Tags: Computer science, Computer vision, OpenCL

April 7, 2019 by hgpu

IPMACC: a framework for translating OpenACC for C API to CUDA, OpenCL, and Intel ISPC

Loop Perforation in OpenACC

multiQueryStream: Concurrent query processing in a GPU-based database system

Concurrent query processing in a GPU-based database system

SYCL-DNN: The SYCL-DNN neural network acceleration library

Accelerated Neural Networks on OpenCL Devices Using SYCL-DNN

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

SYCL-BLAS: An implementation of BLAS using the SYCL open standard for acceleration on OpenCL devices

Cross-Platform Performance Portability Using Highly Parametrized SYCL Kernels

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

The Study of the OpenCL Processing Models for the FPGA Device

The Study of the OpenCL Processing Models for the FPGA Devices

TonY: a framework to natively run deep learning frameworks on Apache Hadoop

TonY: An Orchestrator for Distributed Machine Learning Jobs

fairseq: Facebook AI Research Sequence-to-Sequence Toolkit written in Python

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

mARGOt: Dynamic Application Autotuning for Self-Aware Approximate Computing

Dynamic Application Autotuning for Self-Aware Approximate Computing

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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

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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