Concept

History of computing hardware (1960s–present)

Related publications (36)

EdgeAI-Aware Design of In-Memory Computing Architectures

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

EPFL2024

From the Graphical Processing Unit (GPU) to computing power: exploring the situated practices of liquid nitrogen overclocking

Drawing from a fieldwork conducted at COMPUTEX Taipei, one of the largest computer expo in the world, this contribution proposes to zoom-in at the level of Graphical Processing Units (GPU) manufacturers and their interactions with computer hardware hobbyis ...

2023

A 3.3-Gb/s SPAD-Based Quantum Random Number Generator

Edoardo Charbon, Pouyan Keshavarzian, Francesco Gramuglia, Mario Stipcevic

Quantum random number generators (QRNGs) are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in or ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Self-heating analysis of monolithically integrated hybrid III-V/Si PIN diode

Kirsten Emilie Moselund

Self-heating is a crucial effect in integrated nanophotonic devices regarding their power consumption. In this work, we employ coupled 3D thermo-electrical simulations to gain insight into the thermal behavior related to traps in a monolithic InP-InGaAs-In ...

SPIE-INT SOC OPTICAL ENGINEERING2022

FPGA-to-CPU Undervolting Attacks

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud

FPGAs are proving useful and attractive for many applications, thanks to their hardware reconfigurability, low power, and high-degree of parallelism. As a result, modern embedded systems are often based on systems-on-chip (SoCs), where CPUs and FPGAs share ...

2022

The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models

Jean-Denis Georges Emile Courcol, Michele Migliore, Genrich Ivaska, Carmen Alina Lupascu, Luca Leonardo Bologna, Shailesh Appukuttan

In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and information processing in individual cells and circuits at different scales of observation. Building data-driven brain models requires th ...

FRONTIERS MEDIA SA2022

Accurate deep neural network inference using computational phase-change memory

Irem Boybat Kara, Evangelos Eleftheriou, Abu Sebastian

In-memory computing using resistive memory devices is a promising non-von Neumann approach for making energy-efficient deep learning inference hardware. However, due to device variability and noise, the network needs to be trained in a specific way so that ...

2020

Performance improvement of chip-level CMOS-integrated ReRAM cells through material optimization

Elmira Shahrabi, Yusuf Leblebici, Tugba Demirci

The integration of the resistive random access memory (ReRAM) with CMOS logic circuitry provides a solution to scaling limitations, and offers promising candidates for use in next generation computing applications. It is challenging to realize a reliable, ...

ELSEVIER SCIENCE BV2019

MATHICSE Technical Report: Time domain room acoustic simulations using a spectral element method

Jan Sickmann Hesthaven

This paper presents a wave-based numerical scheme based on a spectral element method, coupled with an implicit-explicit Runge-Kutta time stepping method, for simulating room acoustics in the time domain. The scheme has certain features which make it highly ...

MATHICSE2019

Time domain room acoustic simulations using the spectral element method

Jan Sickmann Hesthaven

ACOUSTICAL SOC AMER AMER INST PHYSICS2019

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