Results 11 to 20 of about 350,213 (359)

Linear Accelerators

open access: yes, 2013
35 pages, contribution to the CAS - CERN Accelerator School: Advanced Accelerator Physics Course, Trondheim, Norway, 18-29 Aug 2013.
Vretenar, Maurizio, Vretenar, M.
openaire   +4 more sources

AvA: Accelerated Virtualization of Accelerators [PDF]

open access: yesProceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, 2020
Applications are migrating en masse to the cloud, while accelerators such as GPUs, TPUs, and FPGAs proliferate in the wake of Moore's Law. These trends are in conflict: cloud applications run on virtual platforms, but existing virtualization techniques have not provided production-ready solutions for accelerators.
Hangchen Yu   +3 more
openaire   +1 more source

Acceleration Methods [PDF]

open access: yesFoundations and Trends® in Optimization, 2021
This monograph covers some recent advances in a range of acceleration techniques frequently used in convex optimization. We first use quadratic optimization problems to introduce two key families of methods, namely momentum and nested optimization schemes. They coincide in the quadratic case to form the Chebyshev method.
Alexandre d'Aspremont   +2 more
openaire   +2 more sources

Comparison between Up-Conversion Detection in Glow-Discharge Detectors and the Schottky Diode for MMW/THz High-Power Single Pulse

open access: yesApplied Sciences, 2021
Generally, glow-discharge detectors (GDD), acting on miniature neon indicator lamps, and Schottky diode detectors serve as efficient, fast, and room-temperature millimeter wave (MMW)/THz detectors.
Adnan Haj Yahya   +4 more
doaj   +1 more source

DNN+NeuroSim V2.0: An End-to-End Benchmarking Framework for Compute-in-Memory Accelerators for On-Chip Training [PDF]

open access: yesIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020
DNN+NeuroSim is an integrated framework to benchmark compute-in-memory (CIM) accelerators for deep neural networks, with hierarchical design options from device-level, to circuit level and up to algorithm level. A python wrapper is developed to interface
Xiaochen Peng   +4 more
semanticscholar   +1 more source

Acceleration modules in linear induction accelerators [PDF]

open access: yesChinese Physics C, 2014
Linear Induction Accelerator (LIA) is a unique type of accelerator, which is capable to accelerate kilo-Ampere beam current to tens of MeV. The LIA acceleration modules, filled with ferrite or ferromagnetic toroid cores, can be conveniently stacked to obtain high energy. During the evolution of LIA, several models for the LIA acceleration module and the
Wang, Shaoheng, Deng, Jianjun
openaire   +2 more sources

Odd entanglement entropy and logarithmic negativity for thermofield double states

open access: yesJournal of High Energy Physics, 2021
We investigate the time evolution of odd entanglement entropy (OEE) and logarithmic negativity (LN) for the thermofield double (TFD) states in free scalar quantum field theories using the covariance matrix approach.
Mostafa Ghasemi   +2 more
doaj   +1 more source

SoK: Fully Homomorphic Encryption Accelerators [PDF]

open access: yesACM Computing Surveys, 2022
Fully Homomorphic Encryption (FHE) is a key technology enabling privacy-preserving computing. However, the fundamental challenge of FHE is its inefficiency, due primarily to the underlying polynomial computations with high computation complexity and ...
Junxue Zhang   +5 more
semanticscholar   +1 more source

Accelerators and the Accelerator Community [PDF]

open access: yesReviews of Accelerator Science and Technology, 2008
In this paper, standing back — looking from afar — and adopting a historical perspective, the field of accelerator science is examined. The subjects explored are: how it grew, what were the forces that made it what it is, where it is now, and what it is likely to be in the future. Clearly, many personal opinions, are offered in this process.
Malamud, Ernest, Sessler, Andrew
openaire   +1 more source

FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review [PDF]

open access: yesIEEE Access, 2019
Due to recent advances in digital technologies, and availability of credible data, an area of artificial intelligence, deep learning, has emerged and has demonstrated its ability and effectiveness in solving complex learning problems not possible before.
Ahmad Shawahna, S. M. Sait, A. El-Maleh
semanticscholar   +1 more source

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