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Albert Reuther
Researcher at Massachusetts Institute of Technology
Publications - 152
Citations - 4542
Albert Reuther is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Computer science & Supercomputer. The author has an hindex of 25, co-authored 142 publications receiving 3976 citations. Previous affiliations of Albert Reuther include Purdue University.
Papers
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Journal ArticleDOI
A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems
Tracy D. Braun,Howard Jay Siegel,N.B. Beck,Ladislau Bölöni,Muthucumaru Maheswaran,Albert Reuther,James Patrick Robertson,Mitchell D. Theys,Bin Yao,Debra Hensgen,Richard F. Freund +10 more
TL;DR: It is shown that for the cases studied here, the relatively simple Min?min heuristic performs well in comparison to the other techniques, and one even basis for comparison and insights into circumstances where one technique will out-perform another.
Proceedings ArticleDOI
A comparison study of static mapping heuristics for a class of meta-tasks on heterogeneous computing systems
Tracy D. Braun,H.J. Siegal,N.B. Beck,Ladislau Bölöni,Muthucumaru Maheswaran,Albert Reuther,J.P. Robertson,Mitchell D. Theys,Bin Yao,Debra Hensgen,Richard F. Freund +10 more
TL;DR: A collection of eleven heuristics from the literature has been selected, implemented, and analyzed under one set of common assumptions and provides one even basis for comparison and insights into circumstances where one technique will outperform another.
Proceedings ArticleDOI
Interactive Supercomputing on 40,000 Cores for Machine Learning and Data Analysis
Albert Reuther,Jeremy Kepner,Chansup Byun,Siddharth Samsi,William Arcand,David Bestor,Bill Bergeron,Vijay Gadepally,Michael Houle,Matthew Hubbell,Michael Jones,Anna Klein,Lauren Milechin,Julia Mullen,Andrew Prout,Antonio Rosa,Charles Yee,Peter Michaleas +17 more
TL;DR: In this paper, the authors demonstrate the capabilities of a 40,000-core supercomputer to launch tens of thousands of TensorFlow and MATLAB/Octave processes in 40 seconds.
Proceedings ArticleDOI
Dynamic distributed dimensional data model (D4M) database and computation system
Jeremy Kepner,William Arcand,William Bergeron,Nadya T. Bliss,Robert A. Bond,Chansup Byun,Gary R. Condon,Kenneth Gregson,Matthew Hubbell,Jonathan Kurz,Andrew McCabe,Peter Michaleas,Andrew Prout,Albert Reuther,Antonio Rosa,Charles Yee +15 more
TL;DR: D4M (Dynamic Distributed Dimensional Data Model) has been developed to provide a mathematically rich interface to tuple stores (and structured query language “SQL” databases) and it is possible to create composable analytics with significantly less effort than using traditional approaches.
Proceedings ArticleDOI
Survey and Benchmarking of Machine Learning Accelerators
TL;DR: This paper surveys the current state of processors and accelerators that have been publicly announced with performance and power consumption numbers, and selects and benchmark two commercially available low size, weight, and power (SWaP) accelerators as these processors are the most interesting for embedded and mobile machine learning inference applications that are most applicable to the DoD and other SWaP constrained users.