Titlebook: Data Orchestration in Deep Learning Accelerators; Tushar Krishna,Hyoukjun Kwon,Ananda Samajdar Book 2020 Springer Nature Switzerland AG 20

diathermy

and the Co-production of Men’s Healthic accelerators have constraints and goals that differ in key ways. It is important to understand in detail how these cause accelerator architects to make different hardware choices. In this chapter, we present a framework for understanding key options, and explore tradeoffs between design effort and cross-project reuse.

发誓放弃

OREX

obstinate

摘要记录

Dataflow and Data Reuse,ning). We show how choices in tiling, scheduling, and partitioning affect the degree to which an accelerator can exploit the . reuse present in the original problem, and formalize these choices into the concepts of . and ..

Charitable

魅力

草本植物

NATAL

Communication in Adopting Moral Normsial step in the design-space exploration loop for DNN accelerators. In this chapter, we discuss the mapping step in further detail, and then examine how microarchitectural models for DNN accelerators can be constructed to evaluate the performance and energy cost of execution of a mapping on the hardware.

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