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Cecile Grezes

dblp:180/3675 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Memory systems · 87% Hardware reliability and fault tolerance · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems › non-volatile memory
magnetic random access memory
0.212016
MTJ variation monitor-assisted adaptive MRAM write · DAC 2016
Memory systems
non-volatile memory
0.212016
MTJ variation monitor-assisted adaptive MRAM write · DAC 2016

Methods — techniques the papers use, named apart from their topics

adaptive write pulse selection · 0.2MTJ variation monitor · 0.2
YearPublicationVenuePosition
2017 Hybrid VC-MTJ/CMOS non-volatile stochastic logic for efficient computing
abstract
In this paper, we propose a non-volatile stochastic computing (SC) scheme using voltage-controlled magnetic tunnel junction (VC-MTJ) and negative differential resistance (NDR). The proposed design includes a VC-MTJ based true stochastic bit stream generator and VC-MTJ and NDR based stochastic adder, multiplier, register, which are experimentally demonstrated using 60nm VC-MTJ and CMOS NDR connected on die. These components are then used to realize FIR filter and AdaBoost (machine-learning algorithm). 3X–37X energy advantage is shown for the proposed SC compared with CMOS binary arithmetic ASIC and SC designs.
Shaodi Wang, Saptadeep Pal, Tianmu Li, Andrew Pan, Cecile Grezes, Pedram Khalili Amiri, Kang L. Wang, Puneet Gupta 0001
DATE5
2016 MTJ variation monitor-assisted adaptive MRAM write
abstract
Spin-transfer torque random access memory (STT-RAM) and magnetoelectric random access memory (MeRAM) are promising non-volatile memory technologies. But STT-RAM and Me RAM both suffer from high write error rate due to thermal fluctuation of magnetization. Temperature and wafer-level process variation significantly exacerbate these problems. In this paper, we propose a design that adaptively selects optimized write pulse for STT-RAM and MeRAM to overcome ambient process and temperature variation. To enable the adaptive write, we design specific MTJ-based variation monitor, which precisely senses process and temperature variation. The monitor is over 10X faster, 5X more energy-efficient, and 20X smaller compared with conventional thermal monitors of similar accuracy. With adaptive write, the write latency of STT-RAM and MeRAM cache are reduced by up to 17% and 59% respectively, and application run time is improved by up to 41%.
Shaodi Wang, Hochul Lee, Cecile Grezes, Pedram Khalili Amiri, Kang L. Wang, Puneet Gupta 0001
DAC3