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Phillip Alpatov

dblp:98/6721 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1997
—ORCID · none

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

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

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
High-performance computing · 61% Parallel and multicore computing · 39%

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

TopicWeightPapersLastEvidence papers
High-performance computing › numerical linear algebra
dense linear algebra
0.011997
PLAPACK Parallel Linear Algebra Package Design Overview · SC 1997
High-performance computing › numerical linear algebra
parallel linear algebra
0.011997
PLAPACK Parallel Linear Algebra Package Design Overview · SC 1997
Parallel and multicore computing
parallel programming models
0.011997
PLAPACK Parallel Linear Algebra Package Design Overview · SC 1997
Parallel and multicore computing › parallel computing
distributed memory computing
0.011997
PLAPACK Parallel Linear Algebra Package Design Overview · SC 1997

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

physically based matrix distribution · 0.0MPI · 0.0
YearPublicationVenuePosition
1997 PLAPACK Parallel Linear Algebra Package Design Overview
abstract
Over the past twenty years, dense linear algebra libraries have gone through three generations of public domain general purpose packages. In the seventies, the first generation of packages were EISPACK and LINPACK, which implemented a broad spectrum of algorithms for solving dense linear eigenproblems and dense linear systems. In the late eighties, the second generation package called LAPACK was developed. This package attains high performance in a portable fashion while also improving upon the functionality and robustness of LINPACK and EISPACK. Finally, since the early nineties, a third generation package which ports LAPACK to distributed memory networks of computers has been underway as part of the ScaLAPACK project.PLAPACK is a maturing fourth generation package which uses a more application-centric view of vector and matrix distribution, Physically Based Matrix Distribution. It also uses an "MPI-like" programming interface that hides distribution and indexing details in opaque objects, provides a natural layering in the library, and provides a straight-forward application interface. In this paper, we give an overview of the design of PLAPACK.
Phillip Alpatov, Gregory S. Baker, H. Carter Edwards, John A. Gunnels, Greg Morrow, James Overfelt, Robert A. van de Geijn
SC1