Data Orchestration in Deep Learning Accelerators (Paperback)

Name: Data Orchestration in Deep Learning Accelerators (Paperback)
Author: Tushar Krishna
ISBN: 9783031006395

Tushar Krishna

Language: English

Published by Springer International Publishing AG, Cham, 2020

3031006399 / 9783031006395

Series: Book 6 of 7 - Synthesis Lectures on Computer Architecture

Softcover
New

See all details

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail

5-star seller

AbeBooks seller since October 12, 2005

View this seller's items

Softcover

Condition: New

£ 53.11

Free Shipping

Ships within U.S.A.

Quantity: 1 available

Add to basket

Free 30-day returns

Save for laterCreate a Want for similar items

Item description from seller

Paperback. 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. This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

Seller Inventory # 9783031006395

Contact seller about this item

Report this item

Title: Data Orchestration in Deep Learning Accelerators (Paperback)
Author: Tushar Krishna
Publisher: Springer International Publishing AG, Cham
Publication year: 2020
Condition: new
Binding: Paperback
Language: English
ISBN 10: 3031006399
ISBN 13: 9783031006395
Series: Book 6 of 7: Synthesis Lectures on Computer Architecture

About the Author

Tushar Krishna is an Assistant Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He received a Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2014. Prior to that, he received an M.S.E in Electrical Engineering from Princeton University in 2009 and a B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT), Delhi in 2007. Before joining Georgia Tech in 2015, he worked as a researcher in the VSSAD Group at Intel in Massachusetts. Dr. Krishna’s research spans computer architecture, interconnection networks, networks-on-chip (NoC), and deep learning accelerators, with a focus on optimizing data movement in modern computing systems. Three of his papers have been selected for IEEE Micro’s Top Picks from Computer Architecture, one more received an honorable mention, and three have won best paper awards. He received the National Science Foundation (NSF) CRII awardin 2018 and both a Google Faculty Award and a Facebook Faculty Award in 2019.

Hyoukjun Kwon is a research scientist at Facebook AR/VR. He received his Ph.D. in Computer Science from Georgia Institute of Technology in 2020, advised by Dr. Tushar Krishna. He received B.S. degrees in Environmental Materials Science and in Computer Science and Engineering from Seoul National University in 2015. His research interests include communication-centric DNN accelerator designs, modeling of DNN accelerator architecture and mapping, NoC for accelerators, and co-optimization of DNN model, mapping, and accelerator architecture. He is actively leading the development of multiple open-source tools and RTLs in the DNN accelerator domain, including MAESTRO, MAERI, Microswitch NoC, and OpenSMART. One of his papers was selected for IEEE Micro’s Top Picks from computer architecture in 2019, one received honorable mention in 2018, and another won the best paper award at HPCA 2020.

Angshuman Parashar is a Senior Research Scientist at NVIDIA. His research interests are in building, evaluating, and programming spatial and data-parallel architectures, with a present focus on automated mapping of machine learning algorithms onto architectures based on explicit decoupled data orchestration. Prior to NVIDIA, he was a member of the VSSAD group at Intel, where he worked with a small team of experts in architecture, languages, workloads, and implementation to design and evaluate a new spatial architecture. Dr. Parashar received his Ph.D. in Computer Science and Engineering from the Pennsylvania State University in 2007, and his B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Delhi in 2002.

Michael Pellauer is a Senior Research Scientist at NVIDIA. His research interest is building domain specific accelerators, with a special emphasis on deep learning and sparse tensor algebra. Prior to NVIDIA, he was a member of the VSSAD group at Intel,where he performed research and advanced development on customized spatial accelerators. Dr. Pellauer holds a Ph.D. from the Massachusetts Institute of Technology in Cambridge, Massachusetts (2010), a Master’s from Chalmers University of Technology in Gothenburg, Sweden (2003), and a Bachelor’s from Brown University in Providence, Rhode Island (1999).

Ananda Samajdar is a Ph.D. student at the school of Electrical and Computer Engineering (ECE) at the Georgia Institute of Technology. He completed his B.Tech. (Hons.) in Electronics and Communication Engineering (ECE) from the Indian Institute of Information Technology, Allahabad India (IIIT-A) in 2013. Before joining Georgia Tech, Anand worked as a VLSI design engineer at Qualcomm Bangalore for three years. Anand’s research interest includes designing custom architecture for efficient and deep learning systems. He has authored a number of papers in top-tier computer architecture conferences. Two of his papers received honorablementions in the IEEE MICRO Top Picks 2019, and one was awarded the best paper award at HPCA 2020. He is also the recipient of the silver medal for the ACM student research competition at ASPLOS 2019.

"About the title" may belong to another edition of this title.

Grand Eagle Retail

Bensenville, IL, U.S.A.

5-star seller

AbeBooks seller since October 12, 2005

Shipping rates within U.S.A.

Item	6 to 14 business days	6 to 16 business days
First item	£ 0.00	£ 0.00

Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

Seller's business information

APOLLO ONLINE CORP.

605 Geddes Street
Wilmington, DE U.S.A. 19805

Contact sellerView this seller's itemsView seller's storefront

Terms of sale

We guarantee the condition of every book as it¿s described on the Abebooks web sites. If you¿ve changed
your mind about a book that you¿ve ordered, please use the Ask bookseller a question link to contact us
and we¿ll respond within 2 business days.
Books ship from California and Michigan.

Right of withdrawal

If you are a consumer you can withdraw from the contract in accordance with the following. Consumer means any natural person who is acting for purposes which are outside his trade, business, craft or profession.

Information regarding the right of withdrawal

Statutory right to withdraw

You have the right to withdraw from this contract within 14 days without giving any reason.

The withdrawal period will expire after 14 days from the day on which you acquire, or a third party other than the carrier and indicated by you acquires, physical possession of the last good or the last lot or piece.

To exercise the right of withdrawal, electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". We will communicate to you an acknowledgement of receipt of such a withdrawal on a durable medium (e.g. by e-mail) without delay.

To meet the withdrawal deadline, it is sufficient for you to send your communication concerning your exercise of the right of withdrawal before the withdrawal period has expired.

Effects of withdrawal

If you withdraw from this contract, we will reimburse to you all payments received from you, including the costs of delivery (except for the supplementary costs arising if you chose a type of delivery other than the least expensive type of standard delivery offered by us).

We may make a deduction from the reimbursement for loss in value of any goods supplied, if the loss is the result of unnecessary handling by you.

We will make the reimbursement without undue delay, and not later than 14 days after the day on which we are informed about your decision to withdraw from this contract.

We will make the reimbursement using the same means of payment as you used for the initial transaction, unless you have expressly agreed otherwise; in any event, you will not incur any fees as a result of such reimbursement.

We may withhold reimbursement until we have received the goods back, or you have supplied evidence of having sent back the goods, whichever is the earliest.

You shall send back the goods or hand them over to Grand Eagle Retail, Bensenville, Illinois, U.S.A., without undue delay and in any event not later than 14 days from the day on which you communicate your withdrawal from this contract to us. The deadline is met if you send back the goods before the period of 14 days has expired. You will have to bear the direct cost of returning the goods. You are only liable for any diminished value of the goods resulting from the handling other than what is necessary to establish the nature, characteristics and functioning of the goods.

Exceptions to the right of withdrawal

The right of withdrawal does not apply to:

The delivery of newspapers, journals or magazines with the exception of subscription contracts; and
The supply of digital content which is not supplied on a tangible medium (e.g. on a CD or DVD) if you accepted when you placed your order that we could start to deliver it, and that you could not withdraw once delivery had started.

Shipping terms

Orders usually ship within 2 business days. All books within the US ship free of charge. Delivery is 4-14 business days anywhere in the United States.

Books ship from California and Michigan.

If your book order is heavy or oversized, we may contact you to let you know extra shipping is required.