Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

M. L. Robinson

dblp:27/1631 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 1994
—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
Parallel and multicore computing · 50% High-performance computing · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Parallel and multicore computing
parallel programming models and runtimes
0.011994
Implementation of a portable and reproducible parallel pseudorandom number generator · SC 1994
High-performance computing
scientific computing systems
0.011994
Implementation of a portable and reproducible parallel pseudorandom number generator · SC 1994

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

cycle splitting · 0.0additive lagged-fibonacci generator · 0.0
YearPublicationVenuePosition
1994 Implementation of a portable and reproducible parallel pseudorandom number generator
abstract
We describe in detail the parallel implementation of a family of additive lagged-Fibonacci pseudorandom number generators. The theoretical structure of these generators is exploited to preserve their well-known randomness properties and to provide a parallel system of distinct cycles. The algorithm presented here solves the reproducibility problem for a far larger class of parallel Monte Carlo applications than has been previously possible. In particular, Monte Carlo applications that undergo "splitting" can be coded to be reproducible, independent both of the number of processors and the execution order of the parallel processes. A library of portable C routines that implements these ideas is also described.>
Daniel V. Pryor, Steven A. Cuccaro, Michael Mascagni, M. L. Robinson
SC4