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L. Susan Blackford

dblp:25/6476 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2001
—ORCID · none

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

Systems, architecture and hardware · 2 · 1 first-authorTheory of computation · 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
2 papers
High-performance computing · 69% Parallel and multicore computing · 14% Distributed systems · 8%

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

TopicWeightPapersLastEvidence papers
High-performance computing › numerical linear algebra
distributed linear algebra
0.012001
Numerical libraries and the grid: the GrADS experiments with ScaLAPACK · SC 2001
High-performance computing
numerical libraries
0.012001
Numerical libraries and the grid: the GrADS experiments with ScaLAPACK · SC 2001
Parallel and multicore computing
MPI
0.011996
ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance · SC 1996
High-performance computing
numerical linear algebra
0.011996
ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance · SC 1996
Distributed systems
grid computing
0.012001
Numerical libraries and the grid: the GrADS experiments with ScaLAPACK · SC 2001
Cloud and datacenter computing › cluster resource management and scheduling
resource scheduling
0.012001
Numerical libraries and the grid: the GrADS experiments with ScaLAPACK · SC 2001

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

performance modeling · 0.0benchmarking · 0.0message passing · 0.0block-partitioned algorithms · 0.0
YearPublicationVenuePosition
2001 Numerical libraries and the grid: the GrADS experiments with ScaLAPACK
abstract
This paper describes an overall framework for the design of numerical libraries on a computational Grid of processors where the processors may be geographically distributed and under the control of a Grid-based scheduling system. A set of experiments are presented in the context of solving systems of linear equations using routines from the ScaLAPACK software collection along with various grid service components, such as Globus, NWS, and Autopilot.
Antoine Petitet, L. Susan Blackford, Jack J. Dongarra, Brett Ellis, Graham E. Fagg, Kenneth Roche, Sathish S. Vadhiyar
SC2
1997 Practical Experience in the Numerical Dangers of Heterogeneous Computing
abstract
Special challenges exist in writing reliable numerical library software for heterogeneous computing environments. Although a lot of software for distributed-memory parallel computers has been written, porting this software to a network of workstations requires careful consideration. The symptoms of heterogeneous computing failures can range from erroneous results without warning to deadlock. Some of the problems are straightforward to solve, but for others the solutions are not so obvious, or incur an unacceptable overhead. Making software robust on heterogeneous systems often requires additional communication. We describe and illustrate the problems encountered during the development of ScaLAPACK and the NAG Numerical PVM Library. Where possible, we suggest ways to avoid potential pitfalls, or if that is not possible, we recommend that the software not be used on heterogeneous networks.
L. Susan Blackford, Andrew J. Cleary, Antoine Petitet, R. Clint Whaley, James Demmel, Inderjit S. Dhillon, H. Ren, Ken Stanley, Jack J. Dongarra, Sven Hammarling
ACM Trans. Math. Softw.1
1996 ScaLAPACK: A Portable Linear Algebra Library for Distributed Memory Computers - Design Issues and Performance
abstract
This paper outlines the content and performance of ScaLAPACK, a collection of mathematical software for linear algebra computations on distributed memory computers. The importance of developing standards for computational and message passing interfaces is discussed. We present the different components and building blocks of ScaLAPACK, and indicate the difficulties inherent in producing correct codes for networks of heterogeneous processors. Finally, this paper briefly describes future directions for the ScaLAPACK library and concludes by suggesting alternative approaches to mathematical libraries, explaining how ScaLAPACK could be integrated into efficient and user-friendly distributed systems.
L. Susan Blackford, Andrew J. Cleary, James Demmel, Inderjit S. Dhillon, Jack J. Dongarra, Sven Hammarling, Greg Henry, Antoine Petitet, Ken Stanley, David W. Walker, R. Clint Whaley
SC1