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2018-2020 Index Proceedings of the IEEE Vol. 106-108
2020
Proceedings of the IEEE
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., and Qi, J., Machine Learning in PET: From Photon Detection to Quantitative Image Reconstruction; JPROC Jan. 2020 51-68 Gonugondla, S.K., see Kang, M., 2251-2275 Gonzalez-De-Aledo, P., see -2039 Gonzalez-Garcia ...
JPROC April 2018 626-660 Good, N., see Martinez Cesena, E.A., 1392-1410 Goodwill, D., see 2232-2245 Gopalakrishnan, K., see 2232-2250 Gorgovan, C., see -2039 Gower, R.M., Schmidt, M., Bach, F., and ...
., +, JPROC Aug. 2019 1537-1562 Addressing Unreliability in Emerging Devices and Non-von Neumann Architectures Using Coded Computing. ...
doi:10.1109/jproc.2020.3040096
fatcat:35vqtzlkgjhzdhds5dbqyccesy
Nonsilicon, Non-von Neumann Computing—Part II
2020
Proceedings of the IEEE
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The section opens with the article titled "Addressing unreliability in emerging devices and non-von Neumann architectures using coded computing," by Dutta et al. ...
By contrast, in the present issue, the article titled "The heterogeneous deep neural network processor with a non-von Neumann architecture" by Shin and Yoo from KAIST, South Korea, suggests a non-von Neumann ...
response to the OSTP Grand Challenge in computing. ...
doi:10.1109/jproc.2020.3001748
fatcat:tfvtbd5grzadhbrojokd27zpbm
On the Reliability of Computing-in-Memory Accelerators for Deep Neural Networks
[article]
2022
arXiv
pre-print
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However, most non-volatile memory (NVM) devices suffer from reliability issues, resulting in a difference between actual data involved in the nvCiM computation and the weight value trained in the data ...
Computing-in-memory with emerging non-volatile memory (nvCiM) is shown to be a promising candidate for accelerating deep neural networks (DNNs) with high energy efficiency. ...
CiM DNN Accelerators
Computing-in-Memory Conventional von-Neumann architecture is not efficient because the cost of data movements between memory and processing units is high. ...
arXiv:2205.13018v1
fatcat:r7nbvcnnqfds7ok3cc7g6k3cfi
Stochastic computation
2010
Proceedings of the 47th Design Automation Conference on - DAC '10
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This paper traces the roots of stochastic computing from the Von Neumann era into its current form. Design and CAD challenges are described. ...
Stochastic computation, as presented in this paper, exploits the statistical nature of application-level performance metrics, and matches it to the statistical attributes of the underlying device and circuit ...
RELEVANT WORK Von Neumann [9] was the first to address the problem of reliable computation in presence of unreliable components. ...
doi:10.1145/1837274.1837491
dblp:conf/dac/ShanbhagAKJ10
fatcat:3rpvtrbr2vanfjqbg43be44ppi
Remarks on neurocybernetics and its links to computing science. To the memory of Prof. Luigi M. Ricciardi
2013
Biosystems (Amsterdam. Print)
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Ricciardi documenting the importance of his contributions in the mathematics of brain, neural nets and neurophysiological models, computational simulations and techniques. ...
This paper explores the origins and content of neurocybernetics and its links to artificial intelligence, computer science and knowledge engineering. ...
Acknowledgments This research has been supported by projects from MICINN (MTM2011-28983-C03-03) and CAM (P2009/ESP-1685). ...
doi:10.1016/j.biosystems.2012.11.003
pmid:23313513
fatcat:vgkarf7dwnbpdnahlxs3liuyie
Trends and Future Directions in Nano Structure Based Computing and Fabrication
2006
Computer Design (ICCD '99), IEEE International Conference on
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In this paper, we review some key issues and trends arising from nanostructure based computing and fabrication, while providing a few examples of defect-tolerant circuits and architectures currently being ...
We end with a discussion on future challenges and direction in nanoscale computing. ...
The nanoPLA is programmed using lithographic scale wires along with stochastically coded nanowire address [9] . ...
doi:10.1109/iccd.2006.4380865
dblp:conf/iccd/Bahar06
fatcat:fehrjg3bkzg6fop3kgca4qnd74
The algorithmic origins of life
2012
Journal of the Royal Society Interface
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is in requires dynamical information and therefore can only be inferred by identifying causal architecture. ...
influence and constrain the dynamics of lower-levels in organizational hierarchies -- may be a major contributor to the hierarchal structure of living systems. ...
Identifying the parallels between biological systems, such as the human nervous system, and computers, and drawing inspiration from Turing's work on universal computation, von Neumann [56] sought a formalism ...
doi:10.1098/rsif.2012.0869
pmid:23235265
pmcid:PMC3565706
fatcat:q2ms5u5nwrdlhioo6qjhpwsfpe
Neuromorphic Spiking Neural Networks and Their Memristor-CMOS Hardware Implementations
2019
Materials
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However, the realization of learning strategies in these systems consumes an important proportion of resources in terms of area and power. ...
Inspired by biology, neuromorphic systems have been trying to emulate the human brain for decades, taking advantage of its massive parallelism and sparse information coding. ...
Introduction The outstanding evolution of computers during the last 50 years has been based on the architecture proposed by Von Neumann in the 1940s [1] . ...
doi:10.3390/ma12172745
pmid:31461877
pmcid:PMC6747825
fatcat:bt6hgscpczd2ldc4xc6np7wsvu
Hardware-Software Co-Design: Not Just a Cliché
2015
Summit on Advances in Programming Languages
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It is time to embrace hardware-software co-design in earnest, to cooperate between programming languages and architecture to upend legacy constraints on computing. ...
As the computing ecosystem moves beyond the predictable yearly advances of Moore's Law, appeals to familiarity and backwards compatibility will become less convincing: fundamental shifts in abstraction ...
Non-volatile main memory is an example of an emerging architectural trend in desperate need of attention from a programming-model perspective. ...
doi:10.4230/lipics.snapl.2015.262
dblp:conf/snapl/SampsonBC15
fatcat:w53z5tuoujcx5eqfyn4c5s5eau
The Human Brain Project and neuromorphic computing
2013
Functional Neurology
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behavior of simple, reliable, very fast, lowpower computing devices embedded in intensely recursive architectures. ...
In order to achieve this, a paradigm shift for computing as a whole is needed, which will see it moving away from current "bit precise" computing models and towards new techniques that exploit the stochastic ...
As the substrate represents a typical non-von Neumann system architecture, the memory required for synaptic weights and cell parameters is distributed in the computing fabric and employs technologies like ...
doi:10.11138/fneur/2013.28.3.191
pmid:24139655
pmcid:PMC3812737
fatcat:lf5taz3vs5bcxhy3jw35elgzae
Neuromorphic Electronic Systems for Reservoir Computing
[article]
2020
arXiv
pre-print
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Due to its computational efficiency and the fact that training amounts to a simple linear regression, both spiking and non-spiking implementations of reservoir computing on neuromorphic hardware have been ...
Here, a review of these experimental studies is provided to illustrate the progress in this area and to address the technical challenges which arise from this specific hardware implementation. ...
I would also like to thank Herbert Jaeger, who provided insight and expertise that greatly assisted this research. ...
arXiv:1908.09572v2
fatcat:cimkbnvyrjc3lhixlyufgmqy3i
A Movable Architecture for Robust Spatial Computing
2012
Computer journal
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For more exotic, longer-term strategies, emerging biochemical and nanoscale computing mechanisms (e.g. [6, 7] ) might one day yield fine-grained robust spatial computers in which billions of devices are ...
The fragility that von Neumann discussed-the long chains of logic with no allowance for error-remains embedded in our approach to computing today. ...
In principle, if robustness and indefinite scalability are ignored, then a Turing machine or a von Neumann machine can be implemented, painfully, in an MFM, and traditional computational effects thus produced-but ...
doi:10.1093/comjnl/bxs129
fatcat:kfnhwe5wpvh4ffenic2u4qzhae
Photonic spike processing: ultrafast laser neurons and an integrated photonic network
[article]
2014
arXiv
pre-print
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Whereas neuromorphic engineering exploits the biophysics of neuronal computation algorithms to provide a wide range of computing and signal processing applications, photonics offer an alternative approach ...
and decision-making. ...
Cognitive computing platforms inspired by the architecture of the brain promise potent advantages in efficiency, fault tolerance and adaptability over von Neumann architectures for tasks involving pattern ...
arXiv:1407.2917v1
fatcat:ybesvgvrizbi7jbvy642diteja
PRINS: Resistive CAM Processing in Storage
[article]
2019
arXiv
pre-print
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2018 pre-print arXiv:1805.09612v2 fatcat:xl72pq4mzbbavmhcige7beqsu4Other Versions
Since this approach replicates von Neumann architecture inside storage, it is exposed to the problems faced by von Neumann architecture, especially the bandwidth wall. ...
We present PRINS, a novel in-data processing-in-storage architecture based on Resistive Content Addressable Memory (RCAM). ...
Associative Processing Associative processor (AP) is a non-von-Neumann inmemory computer [76] . ...
arXiv:1805.09612v3
fatcat:gjgbvqf3ebc6lhn5abuipkhfey
Design and architectures for dependable embedded systems
2011
Proceedings of the seventh IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis - CODES+ISSS '11
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architecture. ...
In addition, we present a new classification on faults, errors, and failures. ...
Furthermore, we would like to thank Philip Axer (TU Braunschweig), Thomas Ebi (KIT), and Holm Rauchfuss (TUM) for support in preparing this paper. ...
doi:10.1145/2039370.2039384
dblp:conf/codes/HenkelBBBBCEEHHHKLMPRSSTTWW11
fatcat:jrd25bf65nfjxbuuuvy3bz6zsm
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