Jul 14, 2018 · In this paper, we define a more comprehensive search space of parallelization strategies for DNNs called SOAP, which includes strategies to parallelize a DNN ...
We introduce SOAP, a more comprehensive search space of parallelization strategies for DNNs that includes strategies to parallelize a. DNN in the Sample, ...
We introduce SOAP, a more comprehensive search space of parallelization strategies for DNNs that includes strategies to parallelize a DNN in the Sample, ...
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Jul 14, 2018 · Abstract. The computational requirements for training deep neu- ral networks (DNNs) have grown to the point that it is.
FlexFlow takes as input a graph of all the operations in the neural network and the topology of the network of devices the neural network will run on.
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DATA PARALLELISM. •Replica of neural network on each device. •Each device processes subset of training data. •After each iteration, parameters are.
Duration: 26:11
Posted: Apr 10, 2019
Posted: Apr 10, 2019
Apr 1, 2019 · Based on it, introduces new techniques and system architectures to simplify and automate ML parallelization. This tutorial is built upon the ...
Table 1: Parallelizable dimensions for different operations. The sample and channel dimension index different samples and neurons in a tensor, respectively.
In this paper, we present QDax, an implementation of MAP-Elites which leverages massive parallelism on accelerators to make QD algorithms more accessible. We ...