The Core Technologies for Deep Learning

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This is the second article in a series taken from the inside HPC Guide to The Industrialization of Deep Learning. Given the compute and data intensive nature of deep learning which has significant overlaps with the needs of the high performance computing market, the TOP500 list provides a good proxy of the current market dynamics and trends.

From the central computation perspective, today’s multicore processor architectures dominate the TOP500 with 91% based on Intel processors. However, looking forwards we can expect to see further developments that may include core CPU architectures such as OpenPOWER and ARM. In addition System on a Chip approaches that combine general purpose processors with technologies such as field programmable gate arrays (FPGAs) and digital signal processors (DSPs) can be expected to play an increasing role in deep learning applications.

Read more at insideHPC