Data Orchestration in Deep Learning Accelerators is popular PDF and ePub book, written by Tushar Krishna in 2022-05-31, it is a fantastic choice for those who relish reading online the Technology & Engineering genre. Let's immerse ourselves in this engaging Technology & Engineering book by exploring the summary and details provided below. Remember, Data Orchestration in Deep Learning Accelerators can be Read Online from any device for your convenience.
Data Orchestration in Deep Learning Accelerators Book PDF Summary
This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators. The End of Moore's Law, coupled with the increasing growth in deep learning and other AI applications has led to the emergence of custom Deep Neural Network (DNN) accelerators for energy-efficient inference on edge devices. Modern DNNs have millions of hyper parameters and involve billions of computations; this necessitates extensive data movement from memory to on-chip processing engines. It is well known that the cost of data movement today surpasses the cost of the actual computation; therefore, DNN accelerators require careful orchestration of data across on-chip compute, network, and memory elements to minimize the number of accesses to external DRAM. The book covers DNN dataflows, data reuse, buffer hierarchies, networks-on-chip, and automated design-space exploration. It concludes with data orchestration challenges with compressed and sparse DNNs and future trends. The target audience is students, engineers, and researchers interested in designing high-performance and low-energy accelerators for DNN inference.
Detail Book of Data Orchestration in Deep Learning Accelerators PDF
- Author : Tushar Krishna
- Release : 31 May 2022
- Publisher : Springer Nature
- ISBN : 9783031017674
- Genre : Technology & Engineering
- Total Page : 158 pages
- Language : English
- PDF File Size : 8,7 Mb
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