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Michael Shulte

dblp:263/7338 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Energy-efficient computing · 41% Emerging computing paradigms · 31% Hardware reliability and fault tolerance · 19%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing
power management
0.622020
Scanning the Issue · Proc. IEEE 2020
A Retrospective and Prospective View of Approximate Computing [Point of View} · Proc. IEEE 2020
Emerging computing paradigms
approximate computing
0.412020
A Retrospective and Prospective View of Approximate Computing [Point of View} · Proc. IEEE 2020
Hardware reliability and fault tolerance › reliability analysis
circuit reliability
0.112020
A Retrospective and Prospective View of Approximate Computing [Point of View} · Proc. IEEE 2020
Integrated circuit design
technology scaling
0.112020
Scanning the Issue · Proc. IEEE 2020

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

technology scaling · 0.4
YearPublicationVenuePosition
2020 Scanning the Issue
abstract
Computing systems have been facing severe technology challenges in recent years with regard to power consumption, circuit reliability, and high performance. For many years, the issues of power consumption and performance have been addressed with the use of technology scaling.However, as Dennard’s scaling tends toward an end, it has become difficult to further improve the performance under the same power constraints. In addition to power, reliability also becomes a critical issue when the feature size of the complementary metal-oxide–semiconductor (CMOS) technology is reduced below 7 nm. Thus, ensuring the complete accuracy of the signal has become increasingly challenging in recent years.
Weiqiang Liu 0001, Maximilian John, Andreas Karrenbauer, Adam Allerhand, Fabrizio Lombardi, Michael Shulte, David J. Miller 0001, Zhen Xiang, George Kesidis, Antti Oulasvirta, Niraj Ramesh Dayama, Morteza Shiripour
Proc. IEEE6
2020 A Retrospective and Prospective View of Approximate Computing [Point of View}
abstract
Computing systems are conventionally designed to operate as accurately as possible. However, this trend faces severe technology challenges, such as power consumption, circuit reliability, and high performance. For nearly half a century, performance and power consumption of computing systems have been consistently improved by relying mostly on technology scaling. As per Dennard's scaling, the size of a transistor has been considerably shrunk and the supply voltage has been reduced over the years, such that circuits operate at higher frequencies but nearly at the same power dissipation level. However, as Dennard's scaling tends toward an end, it is difficult to further improve performance under the same power constraints. Power consumption has been a major concern, and it is now an industry-wide problem of critical importance. In addition to power, reliability deteriorates when the feature size of complementary metal-oxide-semiconductor (CMOS) technology is reduced below 7 nm, because parameter variations and faults at advanced nanoscales become difficult to control and prevent. Thus, to ensure the complete accuracy of signals, logic values, devices, and interconnects, manufacturing and verification costs will increase significantly.
Weiqiang Liu 0001, Fabrizio Lombardi, Michael Shulte
Proc. IEEE3