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Improving the Performance of the Contextual Spaces Re-Ranking Algorithm on Heterogeneous Systems

Flavia Pisani, Daniel C. G. Pedronette, Ricardo da S. Torres, Edson Borin

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Tags: Algorithms, ATI, ATI Radeon HD 6550, Computer science, Heterogeneous systems, List ranking, OpenCL

September 5, 2016 by hgpu

Hybrid Multicore Algorithms for Some Semi-Numerical Applications and Graphs

Dip Sankar Banerjee

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Tags: Algorithms, Cell processor, Computer science, CUDA, Distributed computing, List ranking, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Sorting, Thesis

January 19, 2015 by hgpu

High-Performance Computing Algorithms for Constructing Inverted Files on Emerging Multicore Processors

Zheng Wei

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Information Retrieval, List ranking, nVidia, nVidia GeForce GTX 480, Tesla C1060, Tesla C2050, Thesis

October 16, 2012 by hgpu

An On-Demand Fast Parallel Pseudo Random Number Generator with Applications

Dip Sankar Banerjee, Aman Kumar Bahl, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, List ranking, Monte Carlo simulation, nVidia, Pseudo-random number generators, Tesla C1060

April 21, 2012 by hgpu

Cost Efficient PageRank Computation using GPU

Praveen K., Vamshi Krishna K., Anil Sri Harsha B., S. Balasubramanian, P.K. Baruah

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Tags: Algorithms, Computer science, CUBLAS, CUDA, List ranking, nVidia, Sparse matrix, Tesla T20

January 24, 2012 by hgpu

Hybrid Algorithms for List Ranking and Graph Connected Components

Dip Sankar Banerjee, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, List ranking, nVidia, Sorting, Tesla C1060

January 8, 2012 by hgpu

Efficient PageRank and SpMV Computation on AMD GPUs

Tianji Wu, Bo Wang, Yi Shan, Feng Yan, Yu Wang, Ningyi Xu

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Tags: ATI, ATI CAL, ATI IL, ATI Radeon HD 5870, ATI Stream, Computer science, List ranking, OpenCL, Sparse matrix

April 1, 2011 by hgpu

Fast and scalable list ranking on the GPU

M. Suhail Rehman, Kishore Kothapalli, P. J. Narayanan

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Tags: Algorithms, Computer science, CUDA, List ranking, nVidia, nVidia GeForce GTX 280

October 27, 2010 by hgpu

Data-Parallel Flattening by Expansion

Data-Parallel Flattening by Expansion

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

IA-SpGEMM: An Input-aware Auto-tuning Framework for Parallel Sparse Matrix-Matrix Multiplication

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

MGPUSim: Enabling Multi-GPU Performance Modeling and Optimization

TensorNetwork: A library for easy and efficient manipulation of tensor networks

TensorNetwork for Machine Learning

triSYCL: Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

SYCL Code Generation for Multigrid Methods

PSST: A Tutorial for Parallelised Scalable Simulations in TensorFlow

Parallel scalable simulations of biological neural networks using TensorFlow: A beginner’s guide

MUSE: Miami University Simulation Environment

Temporospatial Epidemic Simulations Using Heterogeneous Computing

Pressure Point Analysis framework

Diagnosing Performance Bottlenecks in HPC Applications

Dynamic Distribution Pruning for Efficient Network Architecture Search

Dynamic Distribution Pruning for Efficient Network Architecture Search

Tinker-HP: High Performance Massively Parallel Evolution of Tinker

Raising the Performance of the Tinker-HP Molecular Modeling Package on Intel’s HPC Architectures: a Living Review [Article v1.0]

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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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