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Candice Astier

dblp:415/8173 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0009-0007-8713-6267ORCID · reported

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

Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

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
Parallel and multicore computing · 50% Distributed systems · 25% Interconnection networks and networks-on-chip · 25%
Theoretical computer science
1 paper
Mathematical optimization · 100%

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

TopicWeightPapersLastEvidence papers
Interconnection networks and networks-on-chip › network topology › tree networks
fat-tree network
0.912025
Assigning Cartesian grid area to processes · HPDC 2025
Parallel and multicore computing
parallel computing
0.912025
Assigning Cartesian grid area to processes · HPDC 2025
Parallel and multicore computing › task allocation
process placement
0.912025
Assigning Cartesian grid area to processes · HPDC 2025
Distributed systems › communication optimization
topology-aware communication
0.912025
Assigning Cartesian grid area to processes · HPDC 2025
Mathematical optimization › discrete optimization
mixed integer linear programming
0.312025
Assigning Cartesian grid area to processes · HPDC 2025

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

operations research · 1.7dynamic programming heuristic · 1.7MILP · 1.7
YearPublicationVenuePosition
2025 Assigning Cartesian grid area to processes
abstract
A topology-aware implementation reduces communication times for parallel programs. MPI supports the distribution of processes on a virtual Cartesian grid via the MPI_Cart_Create function. In such situation, communications between process mostly occur between those in charge of adjacent cells. Thus, placing such processes close one to another reduces the risk of congestion. Using operations research techniques and tools, we compute process placements that realize this objective. We present two solutions: a mathematical modeling of this problem, that we then linearize to compute an optimal solution with a MILP solver; or a heuristic based on a dynamic programming algorithm that provides either an optimal guillotine solution or a good quality solution depending on the networks. This work is based on fat-tree topologies to validate the methods and hypotheses of this work.
Candice Astier, Devan Sohier, Antoine Capra
HPDC1