Filters








12 Hits in 5.0 sec

A methodology for the design of dynamic accuracy operators by runtime back bias

Daniele Jahier Pagliari, Yves Durand, David Coriat, Anca Molnos, Edith Beigne, Enrico Macii, Massimo Poncino
2017 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017  
We demonstrate our approach on a state-of-the-art 28nm FDSOI technology, exploiting the strong effect of back biasing on threshold voltage.  ...  Mobile and IoT applications must balance increasing processing demands with limited power and cost budgets.  ...  UTBB FDSOI and Back-Biasing The proposed solution to overcome the limitations of DVAS is demonstrated on 28nm Ultra-Thin Body and Box (UTBB) FDSOI technology [16] .  ... 
doi:10.23919/date.2017.7927165 dblp:conf/date/PagliariDCMBMP17 fatcat:gqrl6ct5hrgrvklg75c2txk4ie

Dependable embedded systems

2008 2008 6th IEEE International Conference on Industrial Informatics  
This Series addresses current and future challenges pertaining to embedded hardware, software, specifications and techniques.  ...  Titles in the Series cover a focused set of embedded topics relating to traditional computing devices as well as hightech appliances used in newer, personal devices, and related topics.  ...  Hideharu Amano at Keio University and its partnering institutions. It was a tremendous help to see to possibilities of FDSOI in silicon very early on.  ... 
doi:10.1109/indin.2008.4618103 fatcat:hal6brsgsjg5rlo3u5xil46pxi

Applications and Techniques for Fast Machine Learning in Science

Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier Duarte, Philip Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci-Memik (+35 others)
2022 Frontiers in Big Data  
This community report is intended to give plenty of examples and inspiration for scientific discovery through integrated and accelerated ML solutions.  ...  The material for the report builds on two workshops held by the Fast ML for Science community and covers three main areas: applications for fast ML across a number of scientific domains; techniques for  ...  These classical techniques mostly found new architecture modules through a manual design search.  ... 
doi:10.3389/fdata.2022.787421 pmid:35496379 pmcid:PMC9041419 fatcat:5w2exf7vvrfvnhln7nj5uppjga

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

Mostafa Rahimiazghadi, Corey Lammie, Jason Kamranr Eshraghian, Melika Payvand, Elisa Donati, Bernabe Linares-Barranco, Giacomo Indiveri
2020 IEEE Transactions on Biomedical Circuits and Systems  
healthcare and biomedical domains.  ...  After providing the required background, we unify the sparsely distributed research on neural network and neuromorphic hardware implementations as applied to the healthcare domain.  ...  Loss function minimization is achieved by optimizing the network parameters (weights and biases).  ... 
doi:10.1109/tbcas.2020.3036081 pmid:33156792 fatcat:rjwfjd7vmvglpk762mqeyiteqq

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications [article]

Mostafa Rahimi Azghadi, Corey Lammie, Jason K. Eshraghian, Melika Payvand, Elisa Donati, Bernabe Linares-Barranco, Giacomo Indiveri
2020 arXiv   pre-print
healthcare and biomedical domains.  ...  After providing the required background, we unify the sparsely distributed research on neural network and neuromorphic hardware implementations as applied to the healthcare domain.  ...  The loss function minimization happens through optimizing the network parameters (weights and biases).  ... 
arXiv:2007.05657v1 fatcat:amqutl3suvgq5nygna4ef36usy

2021 Index IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 68

2021 IEEE Transactions on Circuits and Systems - II - Express Briefs  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  Yan, D., +, TCSII July 2021 2665-2669 A Sub-μ W Reversed-Body-Bias 8-bit Processor on 65-nm Silicon-on-Thin-Box (SOTB) for IoT Applications.  ... 
doi:10.1109/tcsii.2022.3144928 fatcat:bm53w7gva5bthholfhhiq4yg3a

Power Optimization of an Iterative Multiuser Detector for Turbo CodedCDMA

P Seema, H N Mishra, Prof Pratihari, M Swati, Patil, P Seema, H N Mishra, Prof Pratihari, M Swati, Patil
2013 International Journal of Emerging Trends in Electrical and Electronics (IJETEE)   unpublished
The optimal decoding schedule is derived dynamically using the power optimized EXIT chart and a Viterbi search algorithm.  ...  We show through simulation that the optimized power levels allow for successful decoding of heavily loaded systems.  ...  To achieve different threshold voltages, a self-substrate bias circuit is used to control the body bias. In the active mode, a nearly zero body bias is applied.  ... 
fatcat:kiwm23tgwzgndmbedjkay7h4w4

UC San Diego UC San Diego Electronic Theses and Dissertations Title Physical Design Methodologies for the More-than-Moore Era

Wei-Ting Chan
2018 unpublished
We categorize and summarize previous works in these domains as follows. Congestion predictors. Taghavi et al.  ...  A much smaller body of work addresses the fundamental question of predicting 3DIC benefits over conventional 2D implementation, and upper-bounding these benefits.  ...  For example, body tissue may be damaged by excessive power dissipation in a poorly designed implantable circuit [64] . Various approaches have been proposed to overcome such energy/power problems.  ... 
fatcat:pltnecor4jap3dts4ppbyxqyly

ILP-Based Identification of Opportunistic Redundant Logic Insertions for Opportunistic Yield Improvement During Early Process Learning

T.-B Chan, W.-T Chan, A Kahng, W.-T Chan, A Kahng, J Li
2017 ACM Journal on Emerging Technologies in Computing Systems   unpublished
We categorize and summarize previous works in these domains as follows. Congestion predictors. Taghavi et al.  ...  min-cut partitioning for T tiers.  ... 
fatcat:eh7vqwuaojciraazwj76hvr3ci

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

Mostafa Rahimi Azghadi, Corey Lammie, Jason K Eshraghian, Melika Payvand, Elisa Donati, Bernabe Linares-Barranco, Giacomo Indiveri
2020
healthcare and biomedical domains.  ...  healthcare and biomedical domains.  ...  The loss function minimization happens through optimizing the network parameters (weights and biases).  ... 
doi:10.5167/uzh-200402 fatcat:lgomoj2k5bhqzbcytyxpoqaloe

Hardware / Software Architectural and Technological Exploration for Energy-Efficient and Reliable Biomedical Devices

Loris Gérard Duch
2018
Reconfigurable and Accelerated Multi-Core System Kernel Selection Rules a) The search for candidate kernels to accelerate starts from the most frequently used and then progressively goes down through the  ...  variability and aging issues, such as the Bias Temperature Instability (BTI).  ...  only for domain-specific and energy-efficient architectures, but also for the whole digital circuit design community.  ... 
doi:10.5075/epfl-thesis-8917 fatcat:ydp5dxq2jrfilefppajsvpej4u

Efficient fault tolerance for selected scientific computing algorithms on heterogeneous and approximate computer architectures [article]

Alexander Schöll, Universität Stuttgart, Universität Stuttgart
2018
The high computational power of heterogeneous computer architectures allows to accelerate applications in these domains, which are often dominated by compute-intensive mathematical tasks.  ...  This thesis provides fault tolerance and approximate computing methods that enable the reliable and efficient execution of linear algebra operations and Conjugate Gradient solvers using heterogeneous and  ...  It is my pleasure to thank those whose encouragement and support allowed me to grow and to fulfill my goals.  ... 
doi:10.18419/opus-9951 fatcat:2jst3yajpbc63oq2bzkp6gasna