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Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Yuan Yuan

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Thesis

February 7, 2017 by hgpu

Spark-GPU: An Accelerated In-Memory Data Processing Engine on Clusters

Yuan Yuan, Meisam Fathi Salmi, Yin Huai, Kaibo Wang, Rubao Lee, Xiaodong Zhang

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 770, Spark, Task scheduling

February 5, 2017 by hgpu

Fast Fourier Transforms over Prime Fields of Large Characteristic and their Implementation on Graphics Processing Units

Davood Mohajerani

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce GTX 760 M, Security, Thesis

February 5, 2017 by hgpu

Clustering Throughput Optimization on the GPU

Michael Gowanlock, Cody M. Rude, David M. Blair, Justin D. Li, Victor Pankratius

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Tags: Algorithms, Clustering, Computer science, CUDA, Databases, nVidia, OpenMP, Tesla K20

February 5, 2017 by hgpu

GraviDy: a GPU modular, parallel N-body integrator

Cristian Maureira-Fredes, Pau Amaro-Seoane

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Tags: Astrophysics, CUDA, Globular clusters, Gravitation, Instrumentation and Methods for Astrophysics, MPI, nVidia, OpenMP, Package, Physics, Tesla C2050, Tesla C2070, Tesla M2050

February 5, 2017 by hgpu

MPI-GPU parallelism in iterative eigensolvers for block-tridiagonal matrices

A. Lamas Davina, J. E. Roman

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Tags: Algorithms, Computer science, CUDA, Factorization, MPI, nVidia, Tesla K80

February 2, 2017 by hgpu

Autotuning GPU Kernels via Static and Predictive Analysis

Robert V. Lim, Boyana Norris, Allen D. Malony

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Tags: Code generation, Computer science, CUDA, nVidia, Performance, PTX, Tesla K20, Tesla M2050, Tesla M40

February 2, 2017 by hgpu

Parallel Implementations of the Cholesky Decomposition on CPUs and GPUs

Joao Paulo Tarasconi Ruschel

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Linear Algebra, Matrix decomposition, nVidia, OpenCL, OpenMP, Package, Performance, Tesla K80, Thesis

January 26, 2017 by hgpu

A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Rui Fan, Ke Xu, Jichang Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980, Package

January 26, 2017 by hgpu

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, Jeff Dean

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Tags: Algorithms, Computer science, CUDA, Deep learning, GPU cluster, Machine learning, Neural networks, nVidia, TensorFlow, Tesla K40

January 26, 2017 by hgpu

DeepBach: a Steerable Model for Bach chorales generation

Gaetan Hadjeres, Francois Pachet

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Keras, nVidia, nVidia GeForce GTX 980 Ti, Package

January 23, 2017 by hgpu

GPGPU Performance Estimation with Core and Memory Frequency Scaling

Qiang Wang, Xiaowen Chu

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Tags: Computer science, CUDA, Hardware, nVidia, nVidia GeForce GTX 980, Performance

January 23, 2017 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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