Results 31 to 40 of about 2,846 (150)

INFLUENCE OF DIETARY MONENSIN AND LASALOCID ON AGE AND WEIGHT OF BARKI RAM AND EWE-LAMBS AT PUBERTY ( [PDF]

Assiut Veterinary Medical Journal, 1997
A number of 18 male and 15 female weaned Barki lambs were used in two experiments to evaluate the comparative effect of dietary monensin or lasalocid on growth rate, rumen fermentation pattern, feed efficiency as well as age and weight at puberty.
M.A. HEGAZY, A.N. ELIAS
doaj   +1 more source

L2C2: Last-level compressed-contents non-volatile cache and a procedure to forecast performance and lifetime.

PLoS ONE, 2023
Several emerging non-volatile (NV) memory technologies are rising as interesting alternatives to build the Last-Level Cache (LLC). Their advantages, compared to SRAM memory, are higher density and lower static power, but write operations wear out the ...
Carlos Escuin, Pablo Ibáñez, Denis Navarro, Teresa Monreal, José M Llabería, Víctor Viñals   +5 more
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Novel Kinds of Random Access Memory and New Vulnerabilities of Computer Aids based on Them

Безопасность информационных технологий, 2014
The article discusses vulnerabilities of computer aids based on existing RAM and mechanisms for restricting exploitation of such vulnerabilities. In addition, the article discusses features and work methods of different RAM.
Alexander Mihaylovich Korotin
doaj  

Neuromorphic computing using non-volatile memory

Advances in Physics: X, 2017
Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path for implementing massively-parallel and highly energy-efficient neuromorphic computing systems.
Geoffrey W. Burr, Robert M. Shelby, Abu Sebastian, Sangbum Kim, Seyoung Kim, Severin Sidler, Kumar Virwani, Masatoshi Ishii, Pritish Narayanan, Alessandro Fumarola, Lucas L. Sanches, Irem Boybat, Manuel Le Gallo, Kibong Moon, Jiyoo Woo, Hyunsang Hwang, Yusuf Leblebici   +16 more
doaj   +1 more source

TTEC: Data Allocation Optimization for Morphable Scratchpad Memory in Embedded Systems

IEEE Access, 2018
Scratchpad memory (SPM) is widely utilized in many embedded systems as a software-controlled on-chip memory to replace the traditional cache. New non-volatile memory (NVM) has emerged as a promising candidate to replace SRAM in SPM, due to its ...
Linbo Long, Qing Ai, Xiaotong Cui, Jun Liu   +3 more
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Rolfe (Daniellia oliveri) seed meal as a protein source in locally produced concentrates for lambs fed low quality basal diet

Journal of the Saudi Society of Agricultural Sciences, 2019
The objective of this study was to determine the effects of replacing different levels of toasted Daniellia oliveri seed meal (TDS) for groundnut cake (GNC) in the diets of fifteen growing 8-month-old ram-lambs (13 ± 0.25 kg body weight (BW)) on growth ...
Sunday Adewale Okunade, Olurotimi Ayobami Olafadehan   +1 more
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Investigating non-volatile memory architectures for neuromorphic systems with CMOS spike-timed synaptic plasticity

Discover Computing
Learning is crucial for the brain’s ability to adapt to changing conditions. We suggest a collection of novel neuromorphic construction circuits, adjustable synapse circuits, and CMOS Spike Based Driven Synaptic Plasticity (CSBDSP) erudition algorithm ...
Joshika Sharma, Shyam Akashe, Govind Murari Upadhyay   +2 more
doaj   +1 more source

Bidirectional Non-Filamentary RRAM as an Analog Neuromorphic Synapse, Part II: Impact of Al/Mo/Pr_0.7Ca_0.3MnO₃ Device Characteristics on Neural Network Training Accuracy

IEEE Journal of the Electron Devices Society, 2018
Neuromorphic computing embraces the “device history” offered by many analog non-volatile memory (NVM) devices to implement the small weight changes computed by a gradient-descent learning algorithm such as backpropagation. Deterministic and
Alessandro Fumarola, Severin Sidler, Kibong Moon, Junwoo Jang, Robert M. Shelby, Pritish Narayanan, Yusuf Leblebici, Hyunsang Hwang, Geoffrey W. Burr   +8 more
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A Multiplierless Architecture for Image Convolution in Memory

Journal of Low Power Electronics and Applications
Image convolution is a commonly required task in machine vision and Convolution Neural Networks (CNNs). Due to the large data movement required, image convolution can benefit greatly from in-memory computing.
John Reuben, Felix Zeller, Benjamin Seiler, Dietmar Fey   +3 more
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A review on selective in-memory computing processors: Potential alternative to AI-driven applications

Results in Engineering
In-memory computing (IMC) is a paradigm-shifting approach to data processing that eliminates the sluggishness of transferring data between memory and processing units. By integrating computation directly within the memory, IMC accelerates performance for
Mohith V, Sakthivel R
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