January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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CPU cores
Most deep learning applications and libraries use a single core CPU unless they are used within a parallelization framework like Message-Passing Interface (MPI), MapReduce, or Spark. For example, CaffeOnSpark (https://github.com/yahoo/CaffeOnSpark) by the team at Yahoo! uses Spark with Caffe for parallelizing network training across multiple GPUs and CPUs. In most normal settings in a single box, one CPU core is enough for deep learning application development.
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