ReRAM-based Machine Learning
Hao Yu, Leibin Ni, Sai Manoj Pudukotai Dinakarrao
Sold by Rarewaves USA, OSWEGO, IL, U.S.A.
AbeBooks Seller since 10 June 2025
New - Hardcover
Condition: New
Ships within U.S.A.
Quantity: Over 20 available
Add to basketSold by Rarewaves USA, OSWEGO, IL, U.S.A.
AbeBooks Seller since 10 June 2025
Condition: New
Quantity: Over 20 available
Add to basketThe transition towards exascale computing has resulted in major transformations in computing paradigms. The need to analyze and respond to such large amounts of data sets has led to the adoption of machine learning (ML) and deep learning (DL) methods in a wide range of applications. One of the major challenges is the fetching of data from computing memory and writing it back without experiencing a memory-wall bottleneck. To address such concerns, in-memory computing (IMC) and supporting frameworks have been introduced. In-memory computing methods have ultra-low power and high-density embedded storage. Resistive Random-Access Memory (ReRAM) technology seems the most promising IMC solution due to its minimized leakage power, reduced power consumption and smaller hardware footprint, as well as its compatibility with CMOS technology, which is widely used in industry. In this book, the authors introduce ReRAM techniques for performing distributed computing using IMC accelerators, present ReRAM-based IMC architectures that can perform computations of ML and data-intensive applications, as well as strategies to map ML designs onto hardware accelerators. The book serves as a bridge between researchers in the computing domain (algorithm designers for ML and DL) and computing hardware designers.
Seller Inventory # LU-9781839530814
The transition towards exascale computing has resulted in major transformations in computing paradigms. The need to analyze and respond to such large amounts of data sets has led to the adoption of machine learning (ML) and deep learning (DL) methods in a wide range of applications.
One of the major challenges is the fetching of data from computing memory and writing it back without experiencing a memory-wall bottleneck. To address such concerns, in-memory computing (IMC) and supporting frameworks have been introduced. In-memory computing methods have ultra-low power and high-density embedded storage. Resistive Random-Access Memory (ReRAM) technology seems the most promising IMC solution due to its minimized leakage power, reduced power consumption and smaller hardware footprint, as well as its compatibility with CMOS technology, which is widely used in industry.
In this book, the authors introduce ReRAM techniques for performing distributed computing using IMC accelerators, present ReRAM-based IMC architectures that can perform computations of ML and data-intensive applications, as well as strategies to map ML designs onto hardware accelerators.
The book serves as a bridge between researchers in the computing domain (algorithm designers for ML and DL) and computing hardware designers.
Hao Yu is a professor in the School of Microelectronics at Southern University of Science and Technology (SUSTech), China. His main research interests cover energy-efficient IC chip design and mmwave IC design. He is a senior member of IEEE and a member of ACM. He has written several books and holds 20 granted patents. He is a distinguished lecturer of IEEE Circuits and Systems and associate editor of Elsevier Integration, the VLSI Journal, Elsevier Microelectronics Journal, Nature Scientific Reports, ACM Transactions on Embedded Computing Systems and IEEE Transactions on Biomedical Circuits and Systems. He is also a technical program committee member of several IC conferences, including IEEE CICC, BioCAS, A-SSCC, ACM DAC, DATE and ICCAD. He obtained his Ph.D. degree from the EE department at UCLA, USA.
Leibin Ni is a Principle engineer at Huawei Technologies, Shenzhen, China. His research interests include emerging nonvolatile memory platforms, computing in-memory architecture, machine learning applications and low power designs. He is a member of IEEE. He received his Ph.D. from the Nanyang Technological University, Singapore.
Sai Manoj Pudukotai Dinakarrao is an assistant professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), USA. His current research interests include hardware security, adversarial machine learning, Internet of things networks, deep learning in resource-constrained environments, in-memory computing, accelerator design, algorithms, design of self-aware many-core microprocessors and resource management in many-core microprocessors. He is a member of IEEE and ACM. He served as a guest editor to IEEE Design and Test Magazine and reviewer for multiple IEEE and ACM journals. Also, he is a technical program committee member of several CAD conferences, including ACM DAC, DATE, ICCAD, ASP-DAC, ESWEEK and many more. He received a Ph.D. degree in Electrical and Electronic Engineering from the Nanyang Technological University, Singapore.
"About this title" may belong to another edition of this title.
If you are a consumer you can cancel 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 CANCELLATION
Statutory Right to cancel
You have the right to cancel this contract within 14 days for any reason.
The cancellation 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 the last good or the last lot or piece.
To exercise the right to cancel, you must inform us, Rarewaves USA, 10100 W Sample Rd, Ste 101, 33065, Coral Springs, Florida, U.S.A., of your decision to cancel this contract by a clear statement (e.g. a letter sent by post, fax or e-mail). You may use the attached model cancellation form, but it is not obligatory. You can also electronically fill in and submit a clear statement on our website, under "My Purchases" in "My Account". If you use this option, we will communicate to you an acknowledgement of receipt of such a cancellation on a durable medium (e.g. by e-mail) without delay.
To meet the cancellation deadline, it is sufficient for you to send your communication concerning your exercise of the right to cancel before the cancellation period has expired.
Effects of cancellation
If you cancel 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 cancel with 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 us or Rarewaves USA, 10100 W Sample Rd, Ste 101, 33065, Coral Springs, Florida, U.S.A., without undue delay and in any event not later than 14 days from the day on which you communicate your cancellation 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 cancellation
The right of cancellation does not apply to:
Model withdrawal form
(complete and return this form only if you wish to withdraw from the contract)
To: (Rarewaves USA, 10100 W Sample Rd, Ste 101, 33065, Coral Springs, Florida, U.S.A.)
I/We (*) hereby give notice that I/We (*) withdraw from my/our (*) contract of sale of the following goods (*)/for the provision of the following goods (*)/for the provision of the following service (*),
Ordered on (*)/received on (*)
Name of consumer(s)
Address of consumer(s)
Signature of consumer(s) (only if this form is notified on paper)
Date
* Delete as appropriate.
Please note that we do not offer Priority shipping to any country.
We currently do not ship to the below countries:
Afghanistan
Bhutan
Brazil
Brunei Darussalam
Channel Islands
Chile
Israel
Lao
Mexico
Russian Federation
Saudi Arabia
South Africa
Yemen
Please do not attempt to place orders with any of these countries as a ship to address - they will be cancelled.
| Order quantity | 8 to 11 business days | 8 to 11 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.