Results 31 to 40 of about 66,767 (182)
X-SRAM: Enabling In-Memory Boolean Computations in CMOS Static Random Access Memories [PDF]
, 2018 Silicon-based Static Random Access Memories (SRAM) and digital Boolean logic have been the workhorse of the state-of-art computing platforms. Despite tremendous strides in scaling the ubiquitous metal-oxide-semiconductor transistor, the underlying ...
Alessio Giacomini (5601440) +7 more
core +7 more sources
Evaluating the reliability of NAND multiplexing with PRISM [PDF]
, 2005 Probabilistic-model checking is a formal verification technique for analyzing the reliability and performance of systems exhibiting stochastic behavior.
Benítez, Isabel +4 more
core +4 more sources
A Processing in Memory Realization Using Quantum Dot Cellular Automata (QCA): Proposal and Implementation [PDF]
Журнал нано- та електронної фізики, 2017 Processing in Memory (PIM) is a computing paradigm that promises enormous gain in processing speed by eradicating latencies in the typical von Neumann architecture.
P.P. Chougule +5 more
doaj +1 more source
Pure Infinitely Self-Modifying Code is Realizable and Turing-complete [PDF]
International Journal of Electronics and Telecommunications, 2018 Although self-modifying code has been shyed away from due to its complexity and discouragement due to safety issues, it nevertheless provides for a very unique obfuscation method and a different perspective on the relationship between data and code.
Gregory Morse
doaj +1 more source
Energy Reports, 2023 The demand for housing and the expansion of urbanization have increased the price of land and vertical growth of buildings, resulting in converting the courtyard and porch to balconies.
Mehrdad Karimimoshaver +4 more
doaj +1 more source
Challenges and Trends of Nonvolatile In-Memory-Computation Circuits for AI Edge Devices
IEEE Open Journal of the Solid-State Circuits Society, 2021 Nonvolatile memory (NVM)-based computing-in-memory (nvCIM) is a promising candidate for artificial intelligence (AI) edge devices to overcome the latency and energy consumption imposed by the movement of data between memory and processors under the von ...
Je-Min Hung +4 more
doaj +1 more source
Direct Feedback Alignment with Sparse Connections for Local Learning [PDF]
, 2019 Recent advances in deep neural networks (DNNs) owe their success to training algorithms that use backpropagation and gradient-descent. Backpropagation, while highly effective on von Neumann architectures, becomes inefficient when scaling to large ...
Crafton, Brian +3 more
core +2 more sources
Von neumann architecture and modern computers
Global Journal of Mathematical Sciences, 2008 No Abstract. Global Journal of Mathematical Sciences Vol. 6 (2) 2007: pp.
Arikpo, I I, Ogban, F U, Eteng, I E
openaire +3 more sources
Neuromorphic computing with multi-memristive synapses
Nature Communications, 2018 Memristive technology is a promising avenue towards realizing efficient non-von Neumann neuromorphic hardware. Boybat et al. proposes a multi-memristive synaptic architecture with a counter-based global arbitration scheme to address challenges associated
Irem Boybat +9 more
doaj +1 more source
Neuromorphic devices based on fluorite‐structured ferroelectrics
InfoMat, 2022 A continuous exponential rise has been observed in the storage and processing of the data that may not curtail in the foreseeable future. The required data processing speed and power consumption are restricted by the buses between the logic and memory ...
Dong Hyun Lee +7 more
doaj +1 more source