Results 11 to 20 of about 118,830,318 (300)

In-memory mechanical computing

Nature Communications, 2023
Mechanical computing requires matter to adapt behavior according to retained knowledge, often through integrated sensing, actuation, and control of deformation.
Tie Mei, Chang Qing Chen
doaj   +5 more sources

Memory-Centric Computing [PDF]

CoRR, 2023
Memory-centric computing aims to enable computation capability in and near all places where data is generated and stored. As such, it can greatly reduce the large negative performance and energy impact of data access and data movement, by fundamentally avoiding data movement and reducing data access latency & energy.
Mutlu, Onur
core   +5 more sources

In-memory hyperdimensional computing [PDF]

Nature Electronics, 2020
Hyperdimensional computing (HDC) is an emerging computational framework that takes inspiration from attributes of neuronal circuits such as hyperdimensionality, fully distributed holographic representation, and (pseudo)randomness. When employed for machine learning tasks such as learning and classification, HDC involves manipulation and comparison of ...
Karuanaratne, Geethan, Le Gallo, Manuel, Cherubini, Giovanni, Benini, Luca; id_orcid0000-0001-8068-3806, Rahimi, Abbas; id_orcid0000-0003-3141-4970, Sebastian, Abu, Sebastian, Abu   +6 more
openaire   +6 more sources

Phase-Change Memory for In-Memory Computing [PDF]

Chemical Reviews
In-memory computing (IMC) is an emerging computational approach that addresses the processor-memory divide in modern computing systems. The core concept is to leverage the physics of memory devices and their array-level organization to perform computations directly within the memory array.
Abu Sebastian, Syed Ghazi Sarwat, Manuel Le Gallo   +2 more
exaly   +4 more sources

Memory devices and applications for in-memory computing [PDF]

Nature Nanotechnology, 2020
Traditional von Neumann computing systems involve separate processing and memory units. However, data movement is costly in terms of time and energy and this problem is aggravated by the recent explosive growth in highly data-centric applications related to artificial intelligence. This calls for a radical departure from the traditional systems and one
Abu Sebastian, Manuel Le Gallo, Riduan Khaddam-Aljameh, Evangelos Eleftheriou   +3 more
openaire   +3 more sources

Advances in Infrared Detectors for In-Memory Sensing and Computing

Photonics
In-memory sensing and computing devices integrate the functionalities of sensors, memory, and processors, offering advantages such as low power consumption, high bandwidth, and zero latency, making them particularly suitable for simulating synaptic ...
Weibo Feng, Tianling Qin, Xin Tang
doaj   +2 more sources

Memory Optimization Method for Parallel Computing Framework Based on Distributed Dataset [PDF]

Jisuanji gongcheng, 2023
With the rapid development of scientific computing and artificial intelligence technology, parallel computing in distributed environment has become an important method for solving large-scale theoretical computing and data processing problems.
XIA Libin, LIU Xiaoyu, JIANG Xiaowei, SUN Gongxing
doaj   +1 more source

Towards memory supporting personal information management tools [PDF]

, 2007
In this article we discuss re-retrieving personal information objects and relate the task to recovering from lapse(s) in memory. We propose that fundamentally it is lapses in memory that impede users from successfully re-finding the information they need.
Ruthven, I., David Elsweiler, Christopher Jones, Ruthven, Ian, Jones, C., Jones, Christopher, Elsweiler, David, Ian Ruthven   +7 more
core   +3 more sources

Cryogenic In-Memory Computing for Quantum Processors Using Commercial 5-nm FinFETs

IEEE Open Journal of Circuits and Systems, 2023
Cryogenic CMOS circuits that efficiently connect the classical domain with the quantum world are the cornerstone in bringing large-scale quantum processors to reality. The major challenges are, however, the tight power budget (in the order of milliwatts)
Shivendra Singh Parihar, Simon Thomann, Girish Pahwa, Yogesh Singh Chauhan, Hussam Amrouch   +4 more
doaj   +1 more source

Compute-in-Memory for Numerical Computations

Micromachines, 2022
In recent years, compute-in-memory (CIM) has been extensively studied to improve the energy efficiency of computing by reducing data movement. At present, CIM is frequently used in data-intensive computing. Data-intensive computing applications, such as all kinds of neural networks (NNs) in machine learning (ML), are regarded as ‘soft’ computing tasks.
Dongyan Zhao, Yubo Wang, Jin Shao, Yanning Chen, Zhiwang Guo, Cheng Pan, Guangzhi Dong, Min Zhou, Fengxia Wu, Wenhe Wang, Keji Zhou, Xiaoyong Xue   +11 more
openaire   +3 more sources