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Deep Learning Processor

Wikipedia

Deep Learning Processor is a specially designed circuitry optimized for deep learning algorithms, usually with separate data memory and dedicated instruction set architecture. Deep Learning Processors are introduced in a wide range of today's commercial infrastructure, from mobile devices to cloud servers. The goal of DLPs is to provide higher efficiency and performance than existing processing devices, i.e., general CPUs and GPUs, when processing deep learning algorithms. Just as GPUs for graphic processing, DLPs leverage the domain-specific knowledge in designing of architectures for deep learning processing. Commonly, most DLPs leverage a large number of computing components to leverage the high data-level parallelism, a relative larger on-chip buffer/memory to leverage the data reuse patterns, and limited data-width operators to leverage the error-resilience of deep learning.

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