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Collaborative Diffusion on the GPU for Path-Finding in Games

Craig McMillan, Emma Hart, Kevin Chalmers

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Tags: AI, Algorithms, CUDA, Games, Graph, Search

April 15, 2015 by craigmcmillan01

Scaling Deep Learning on GPU and Knights Landing clusters

Scaling Deep Learning on GPU and Knights Landing clusters

Gpufit: GPU-accelerated Levenberg-Marquardt curve fitting in CUDA

Gpufit: An open-source toolkit for GPU-accelerated curve fitting

GARDENIA: Graph Analytics Repository for Designing Next-Generation Accelerators

GARDENIA: A Domain-specific Benchmark Suite for Next-generation Accelerators

GPU-benchmarks

Using Graph Properties to Speed-up GPU-based Graph Traversal: A Model-driven Approach

bit-reversal-methods

Practically efficient methods for performing bit-reversed permutation in C++11 on the x86-64 architecture

bifrost: A stream processing framework for high-throughput applications

Bifrost: a Python/C++ Framework for High-Throughput Stream Processing in Astronomy

NEMATUS: Open-Source Neural Machine Translation in Theano

Deep Architectures for Neural Machine Translation

ParTeCL: parallel testing using OpenCL

ParTeCL: parallel testing using OpenCL

DenseNet: Densely Connected Convolutional Networks

Memory-Efficient Implementation of DenseNets

SVMbenchmark: CUDA and OpenCL SVM training benchmark

A Comparison of Support Vector Machines Training GPU-Accelerated Open Source Implementations

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