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Publications associées (295)

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Gain-cell embedded DRAM (GC-eDRAM) is a high-density logic-compatible alternative to conventional static random-access memory (SRAM) and embedded DRAM (eDRAM). However, GC-eDRAM suffers from a reduced data retention time (DRT) at deeply-scaled process node ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Lawful Interception (LI) is a legal obligation of Communication Service Providers (CSPs) to provide interception capabilities to Law Enforcement Agencies (LEAs) in order to gain insightful data from network communications for criminal proceedings, e.g., ne ...

New York2023

Effective Inhibition of TDP-43 Aggregation by Native State Stabilization

Hilal Lashuel, Yllza Jasiqi, Lixin Yang

Preventing the misfolding or aggregation of transactive response DNA binding protein with 43 kDa (TDP-43) is the most actively pursued disease-modifying strategy to treat amyotrophic lateral sclerosis and other neurodegenerative diseases. In this work, we ...

Weinheim2023

Cultural healing through computational crisis: disruption as a catalyst for alternate technologies

Our presentation will take the form of an interactive dialogue centred around the ramifications of electronic devices: tackled both from our Canadian (Cyrus Khalatbari) and Ghanaian (Akwasi Afrane) arts and design perspectives. Developed moreover as a conv ...

2023

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Numerical simulations explore a possible tightly baffled, long-legged divertor (TBLLD) concept in a future upgrade of the tokamak à configuration variable (TCV). The SOLPS-ITER code package is used to compare the exhaust performance of several TBLLD config ...

2023

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

David Atienza Alonso, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang, Ali Pahlevan

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

2022

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Enumerating simple cycles has important applications in computational biology, network science, and financial crime analysis. In this work, we focus on parallelising the state-of-the-art simple cycle enumeration algorithms by Johnson and Read-Tarjan along ...

arXiv2022

ALPINE: Analog In-Memory Acceleration with Tight Processor Integration for Deep Learning

David Atienza Alonso, Marina Zapater Sancho, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Irem Boybat Kara, Yasir Mahmood Qureshi, Joshua Alexander Harrison Klein, Abu Sebastian

Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate matrix-vector multiplications, which dominate these applications’ run-time. ...

2022

STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale

James Gonzalo King, Pramod Shivaji Kumbhar, Iain Hepburn, Weiliang Chen, Tristan Mathieu Carel, Alessandro Cattabiani, Nicola Cantarutti, Omar Awile, Christos Kotsalos, Samuel Marie A Melchior, Baudouin Paul Michel Maria Joseph Del Marmol, Giacomo Castiglioni

Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parallel imp ...

FRONTIERS MEDIA SA2022

Nonlinear Inverse Problems in Quantitative Phase Imaging

Thanh-An Michel Pham

The topic of this thesis is the development of new algorithmic reconstruction methods for quantitative phase imaging (QPI). In the past decade, advanced QPI has emerged as a valuable tool to study label-free biological samples and uncover their 3D structur ...

EPFL2022

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