R
Robert Schreiber
Researcher at Hewlett-Packard
Publications - 185
Citations - 13234
Robert Schreiber is an academic researcher from Hewlett-Packard. The author has contributed to research in topics: Matrix (mathematics) & Shared memory. The author has an hindex of 49, co-authored 182 publications receiving 12755 citations. Previous affiliations of Robert Schreiber include Ames Research Center & Cornell University.
Papers
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Journal ArticleDOI
The Nas Parallel Benchmarks
David H. Bailey,Eric Barszcz,John T. Barton,D. S. Browning,Russell Carter,Leonardo Dagum,Rod Fatoohi,Paul O. Frederickson,T. A. Lasinski,Robert Schreiber,Horst D. Simon,V. Venkatakrishnan,Sisira Weeratunga +12 more
TL;DR: A new set of benchmarks has been developed for the performance evaluation of highly parallel supercom puters that mimic the computation and data move ment characteristics of large-scale computational fluid dynamics applications.
Book ChapterDOI
Large-Scale Parallel Collaborative Filtering for the Netflix Prize
TL;DR: This paper describes a CF algorithm alternating-least-squares with weighted-?-regularization(ALS-WR), which is implemented on a parallel Matlab platform and shows empirically that the performance of ALS-WR monotonically improves with both the number of features and thenumber of ALS iterations.
Journal ArticleDOI
Corona: System Implications of Emerging Nanophotonic Technology
Dana M. Vantrease,Robert Schreiber,Matteo Monchiero,Moray McLaren,Norman P. Jouppi,Marco Fiorentino,Al Davis,Nathan Binkert,Raymond G. Beausoleil,Jung Ho Ahn +9 more
TL;DR: This work believes that in comparison with an electrically-connected many-core alternative that uses the same on-stack interconnect power, Corona can provide 2 to 6 times more performance on many memory intensive workloads, while simultaneously reducing power.
Book
The High Performance Fortran Handbook
TL;DR: High Performance Fortran is a set of extensions to Fortran expressing parallel execution at a relatively high level that brings the convenience of sequential Fortran a step closer to today's complex parallel machines.
Journal ArticleDOI
Sparse matrices in matlab: design and implementation
TL;DR: The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations, and nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user.