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Steve Solomon

dblp:76/522 · DBLP profile ↗
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4ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

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

Human-computer interaction and ubiquitous computing · 2Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 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
Energy-efficient computing · 44% Cloud and datacenter computing · 44% Distributed systems · 13%
Artificial intelligence
1 paper
Trustworthy machine learning · 100%

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

TopicWeightPapersLastEvidence papers
Energy-efficient computing
datacenter power management
0.512021
Flex: High-Availability Datacenters With Zero Reserved Power · ISCA 2021
Cloud and datacenter computing › resource allocation
workload allocation
0.512021
Flex: High-Availability Datacenters With Zero Reserved Power · ISCA 2021
Distributed systems
fault tolerance
0.112021
Flex: High-Availability Datacenters With Zero Reserved Power · ISCA 2021
Machine learning › Trustworthy machine learning
interpretability
0.112006
Building Explainable Artificial Intelligence Systems · AAAI 2006

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

offline workload placement · 0.5failure monitoring · 0.5
YearPublicationVenuePosition
2021 Flex: High-Availability Datacenters With Zero Reserved Power
abstract
Cloud providers, like Amazon and Microsoft, must guarantee high availability for a large fraction of their workloads. For this reason, they build datacenters with redundant infrastructures for power delivery and cooling. Typically, the redundant resources are reserved for use only during infrastructure failure or maintenance events, so that workload performance and availability do not suffer. Unfortunately, the reserved resources also produce lower power utilization and, consequently, require more datacenters to be built. To address these problems, in this paper we propose "zero-reserved-power" datacenters and the Flex system to ensure that workloads still receive their desired performance and availability. Flex leverages the existence of software-redundant workloads that can tolerate lower infrastructure availability, while imposing minimal (if any) performance degradation for those that require high infrastructure availability. Flex mainly comprises (1) a new offline workload placement policy that reduces stranded power while ensuring safety during failure or maintenance events, and (2) a distributed system that monitors for failures and quickly reduces the power draw while respecting the workloads’ requirements, when it detects a failure. Our evaluation shows that Flex produces less than 5% stranded power and increases the number of deployed servers by up to 33%, which translates to hundreds of millions of dollars in construction cost savings per datacenter site. We end the paper with lessons from our experience bringing Flex to production in Microsoft’s datacenters.
Chaojie Zhang 0001, Alok Gautam Kumbhare, Ioannis Manousakis, Deli Zhang, Pulkit A. Misra, Rod Assis, Kyle Woolcock, Nithish Mahalingam, Brijesh Warrier, David Gauthier, Lalu Kunnath, Steve Solomon, Osvaldo Morales, Marcus Fontoura, Ricardo Bianchini
ISCA12
2006 Building Explainable Artificial Intelligence Systems
Mark G. Core, H. Chad Lane, Michael van Lent, Dave Gomboc, Steve Solomon, Milton Rosenberg
AAAI5
2006 Reflective Tutoring for Immersive Simulation
H. Chad Lane, Mark G. Core, Dave Gomboc, Steve Solomon, Michael van Lent, Milton Rosenberg
Intelligent Tutoring Systems4
2005 Explainable Artificial Intelligence for Training and Tutoring
H. Chad Lane, Mark G. Core, Michael van Lent, Steve Solomon, Dave Gomboc
AIED4