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An unsupervised parallel genetic cluster algorithm for graphics processing units

D. Hendricks, D. Cieslakiewicz, D. Wilcox, T. Gebbie

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Tags: Clustering, Computational finance, CUDA, Genetic programming, nVidia, nVidia GeForce 560 Ti, nVidia GeForce 660 Ti, nVidia GeForce GTX 660 M

March 23, 2014 by hgpu

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high performance computing on graphics processing units: hgpu.org

An unsupervised parallel genetic cluster algorithm for graphics processing units

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schnaps: a finite element solver

GPU-benchmarks

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

SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks

SWIFOLD: Smith-Waterman implementation on FPGA with OpenCL for long DNA sequences

Spatter: Benchmark for measuring the performance of sparse and irregular memory access

StePS: Stereographically Projected Cosmological Simulations

AMGCL:C++ library for solving large sparse linear systems with algebraic multigrid method

PAstudy

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International Conference on Frontiers of Neural Networks (ICFNN), 2019

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3rd World Conference on Clinical Research and Biomarkers, 2019

3rd International Conference on Vision, Image and Signal Processing (ICVISP), 2019

3rd International Symposium on Intelligent Unmanned Systems and Artificial Intelligence (SIUSAI), 2019