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Scaling Deep Learning on GPU and Knights Landing clusters

Yang You, Aydin Buluc, James Demmel

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Tags: Cloud, Computer science, Deep learning, GPU cluster, Intel Xeon Phi, Machine learning, Neural networks, nVidia, Package, PC cluster, Tesla K80, Tesla M100

August 17, 2017 by hgpu

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high performance computing on graphics processing units: hgpu.org

Recent source codes

SolidTextureNets

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

deepnetts: Deep Netts Pure Java Deep Learning Engine

PASTA: A Parallel Sparse Tensor Algorithm Benchmark Suite

TACO: The Tensor Algebra Compiler (taco) computes sparse tensor expressions on CPUs and GPUs

OpenCL-FPGA-LLVM: LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

CUDAnative.jl: Julia support for native CUDA programming

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Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

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