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A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Mark W. Lewis

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Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTS 780 Ti

June 5, 2017 by hgpu

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high performance computing on graphics processing units: hgpu.org

A Diversified Multi-Start Algorithm for Unconstrained Binary Quadratic Problems Leveraging the Graphics Processor Unit

Recent source codes

HLS4ML

cytonRL: reinforcement learning, deep Q-network, double DQN, dueling DQN, prioritized experience replay

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

HCC: Open Source, Optimizing C++ Compiler for Heterogeneous Compute for the ROCm GPU Computing Platform

pynufft: Python non-uniform fast Fourier transform (NUFFT)

MALBEC: a new CUDA-C ray-tracer in General Relativity

Volna-OP2: OP2 port of the original Volna code

CuLDA_CGS: Solving Large-scale LDA Problems on GPUs

MeterPU: Generic Portable Measurement Framework for Multicore CPU and Multi-GPU Systems

GHOST: General, Hybrid and Optimized Sparse Toolkit

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Featured events

International Conference on Biomedicine & Pharmacotherapy, 2018

8th International Workshop on Computer Science and Engineering (WCSE’18), 2018

International Conference on Robotics, Artificial Intelligence, Automation and Mechatronics, 2018

The 3rd IEEE International Conference on Image, Vision and Computing (ICIVC), 2018

The 2th International Conference on Robotics and Automation Sciences (ICRAS), 2018