A 24 kb Single-Well Mixed 3T Gain-Cell eDRAM with Body-Bias in 28 nm FD-SOI for Refresh-Free DSP Applications

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

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

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

Method for reading and writing unreliable memories and a corresponding memory controller device and memory

Andreas Peter Burg, Reza Ghanaatian Jahromi

A method of accessing a memory space of a memory device with a decoder, the memory space having faults, including the steps of performing a memory access operation by an electronic device to a access a logical memory space of the memory device, and randomi ...

2022

HPCache: Memory-Efficient OLAP Through Proportional Caching

Anastasia Ailamaki, Periklis Chrysogelos, Hamish Mcniece Hill Nicholson

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution ...

ACM2022

Impact of Interface Traps in Floating-Gate Memory Based on Monolayer MoS2

Andras Kis, Guilherme Migliato Marega

Two-dimensional materials (2DMs) have found potential applications in many areas of electronics, such as sensing, memory systems, optoelectronics, and power. Despite an intense experimental work, the literature is lacking of accurate modeling of nonvolatil ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Andras Kis, Aleksandra Radenovic, Zhenyu Wang, Guilherme Migliato Marega, Mukesh Kumar Tripathi

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

Tuning paradigm of external stimuli driven electronic, optical and magnetic properties in hybrid perovskites and metalorganic complexes br

Mohammad Khaja Nazeeruddin

We have witnessed a wide range of theoretical as well as experimental investigations to envisage external stimuli induced changes in electronic, optical and magnetic properties in the metal organiccomplexes, while hybrid perovskites have recently joined th ...

ELSEVIER SCI LTD2022

VWR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices

David Atienza Alonso, Benoît Walter Denkinger, Miguel Peon Quiros

Edge-computing requires high-performance energy-efficient embedded systems. Fixed-function or custom accelerators, such as FFT or FIR filter engines, are very efficient at implementing a particular functionality for a given set of constraints. However, the ...

ASSOC COMPUTING MACHINERY2022

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

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

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

AstriFlash: A Flash-Based System for Online Services

Babak Falsafi, Mark Johnathon Sutherland, Siddharth Gupta, Lei Yan, Yunho Oh

Modern datacenters host datasets in DRAM to offer large-scale online services with tight tail-latency requirements. Unfortunately, as DRAM is expensive and increasingly difficult to scale, datacenter operators are forced to consider denser storage technolo ...

2023

An Energy-Efficient Bridge-to-Digital Converter for Implantable Pressure Monitoring Systems

Marco Mattavelli, Catherine Dehollain, Diego Ruben Barrettino, Franco Maloberti, Kerim Türe, Mustafa Besirli

This paper presents an energy-efficient, duty-cycled, and spinning excitation bridge-to-digital converter (BDC) designed for implantable pressure sensing systems. The circuit provides the measure of the pulmonary artery pressure that is particularly releva ...

2022

Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Flavio Ponzina, Marco Antonio Rios

The growing popularity of edge computing has fostered the development of diverse solutions to support Artificial Intelligence (AI) in energy-constrained devices. Nonetheless, comparatively few efforts have focused on the resiliency exhibited by AI workload ...

2022

Request, Coalesce, Serve, and Forget: Miss-Optimized Memory Systems for Bandwidth-Bound Cache-Unfriendly Applications on FPGAs

Paolo Ienne, Mikhail Asiatici

Applications such as large-scale sparse linear algebra and graph analytics are challenging to accelerate on FPGAs due to the short irregular memory accesses, resulting in low cache hit rates. Nonblocking caches reduce the bandwidth required by misses by re ...

ASSOC COMPUTING MACHINERY2022

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