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Yevgeniy Ryasnianskiy

dblp:252/4626 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

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

Systems, architecture and hardware · 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
Interconnection networks and networks-on-chip · 65% Electronic design automation · 22% High-performance computing · 6%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interconnection networks and networks-on-chip › routing algorithms
adaptive routing
0.412019
Topology-custom UGAL routing on dragonfly · SC 2019
Interconnection networks and networks-on-chip › network topology › low-diameter topology
dragonfly network
0.412019
Topology-custom UGAL routing on dragonfly · SC 2019
Interconnection networks and networks-on-chip
network topology
0.412019
Topology-custom UGAL routing on dragonfly · SC 2019
Electronic design automation › physical design
routing
0.412019
Topology-custom UGAL routing on dragonfly · SC 2019
Performance modeling and evaluation › network performance analysis
interconnection network performance
0.112019
Topology-custom UGAL routing on dragonfly · SC 2019
High-performance computing
supercomputing
0.112019
Topology-custom UGAL routing on dragonfly · SC 2019

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

topology-custom path computation · 0.4load-balance routing · 0.4
YearPublicationVenuePosition
2019 Topology-custom UGAL routing on dragonfly
abstract
The Dragonfly network has been deployed in the current generation supercomputers and will be used in the next generation supercomputers. The Universal Globally Adaptive Load-balance routing (UGAL) is the state-of-the-art routing scheme for Dragonfly. In this work, we show that the performance of the conventional UGAL can be further improved on many practical Dragonfly networks, especially the ones with a small number of groups, by customizing the paths used in UGAL for each topology. We develop a scheme to compute the custom sets of paths for each topology and compare the performance of our topology-custom UGAL routing (T-UGAL) with conventional UGAL. Our evaluation with different UGAL variations and different topologies demonstrates that by customizing the routes, T-UGAL offers significant improvements over UGAL on many practical Dragonfly networks in terms of both latency when the network is under low load and throughput when the network is under high load.
Md. Shafayat Rahman, Saptarshi Bhowmik, Yevgeniy Ryasnianskiy, Xin Yuan 0001, Michael Lang 0003
SC3