Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design
|
Not currently available
Data Orchestration in Deep Learning Accelerators (Paperback)
Loot Price: R1,987
Discovery Miles 19 870
|
|
Data Orchestration in Deep Learning Accelerators (Paperback)
Series: Synthesis Lectures on Computer Architecture
Supplier out of stock. If you add this item to your wish list we will let you know when it becomes available.
|
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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.