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Exact Selectivity Computation for Modern In-Memory Database Query Optimization

Jun Hyung Shin, Florin Rusu, Alex Suhan

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Tags: Computer science, CUDA, Databases, nVidia, Package, Tesla K80

January 13, 2019 by hgpu

BitCracker: BitLocker meets GPUs

Elena Agostini, Massimo Bernaschi

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Tags: AES, ATI, ATI Radeon HD 7990, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan X, OpenCL, Package, Security, Tesla K80, Tesla P100, Tesla V100

January 13, 2019 by hgpu

HG-Caffe: Mobile and Embedded Neural Network GPU (OpenCL) Inference Engine with FP16 Supporting

Zhuoran Ji

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Tags: Caffe, Computer science, Deep learning, Machine learning, Neural networks, OpenCL, Package

January 13, 2019 by hgpu

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

Ao Ren, Tianyun Zhang, Shaokai Ye, Jiayu Li, Wenyao Xu, Xuehai Qian, Xue Lin, Yanzhi Wang

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Tags: Caffe, Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla P100

January 6, 2019 by hgpu

Towards Automatic Transformation of Legacy Scientific Code into OpenCL for Optimal Performance on FPGAs

Wim Vanderbauwhede, Syed Waqar Nabi

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Tags: Compilers, Computer science, Fortran, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenACC, OpenCL, OpenMP, Package

January 6, 2019 by hgpu

Speeding-up the Verification Phase of Set Similarity Joins in the GPGPU paradigm

Christos Bellas, Anastasios Gounaris

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

December 30, 2018 by hgpu

wav2letter++: The Fastest Open-source Speech Recognition System

Vineel Pratap, Awni Hannun, Qiantong Xu, Jeff Cai, Jacob Kahn, Gabriel Synnaeve, Vitaliy Liptchinsky, Ronan Collobert

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Speech recognition, Tesla V100

December 23, 2018 by hgpu

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

Reuben D. Budiardja, Christian Y. Cardall

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Tags: cfd, CUDA, Fluid dynamics, Fortran, MPI, nVidia, OpenMP, Package, Physics, Tesla V100

December 23, 2018 by hgpu

Optimization of a discontinuous finite element solver with OpenCL and StarPU

Philippe Helluy, Laura Mendoza, Bruno Weber

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Tags: Algorithms, Computer science, Hybrid computing, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro P 6000, OpenCL, Package, Task scheduling

December 9, 2018 by hgpu

Mix-and-Match: A Model-driven Runtime Optimisation Strategy for BFS on GPUs

Merijn Verstraaten, Ana Lucia Varbanescu, Cees de Laat

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Tags: Breadth-First Search, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

December 2, 2018 by hgpu

Performance Portability Challenges for Fortran Applications

Abigail Hsu, David Neill Asanza, Joseph A. Schoonover, Zach Jibben, Neil N. Carlson, Robert Robey

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Tags: Computer science, CUDA, Finite difference, Fortran, nVidia, OpenMP, Package, performance portability, Tesla P100, Tesla V100

December 2, 2018 by hgpu

CLort: High Throughput and Low Energy Network Intrusion Detection on IoT Devices with Embedded GPUs

Charalampos Stylianopoulos, Linus Johansson, Oskar Olsson, Magnus Almgren

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Tags: ARM, Computer science, IoT, OpenCL, Package, Security

November 25, 2018 by hgpu

MapD Core database

Exact Selectivity Computation for Modern In-Memory Database Query Optimization

BitCracker: the first open source password cracking tool for memory units encrypted with BitLocker

BitCracker: BitLocker meets GPUs

caffe-android-opencl-fp16: Optimised Caffe with OpenCL supporting for less powerful devices such as mobile phones

HG-Caffe: Mobile and Embedded Neural Network GPU (OpenCL) Inference Engine with FP16 Supporting

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

ADMM-NN: An Algorithm-Hardware Co-Design Framework of DNNs Using Alternating Direction Method of Multipliers

AutoParallel-Fortran: A domain specific, automatically parallelising source-to-source compiler for Fortran-95 that takes scientific Fortran as input and produces parallel Fortran/OpenCL

Towards Automatic Transformation of Legacy Scientific Code into OpenCL for Optimal Performance on FPGAs

gpussjoin: Set Similarity joins in the GPGPU paradigm

Speeding-up the Verification Phase of Set Similarity Joins in the GPGPU paradigm

wav2letter: Facebook AI Research Automatic Speech Recognition Toolkit

wav2letter++: The Fastest Open-source Speech Recognition System

GenASiS_Basics: Object-oriented Utilitarian Functionality for Large-scale Physics Simulations

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

schnaps: a finite element solver

Optimization of a discontinuous finite element solver with OpenCL and StarPU

GPU-benchmarks

Mix-and-Match: A Model-driven Runtime Optimisation Strategy for BFS on GPUs

See all packages

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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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