Julia implementation of the Dynamic Distributed Dimensional Data Model

Author(s)
Chen, Alexander Y.; Edelman, Alan; Kepner, Jeremy; Gadepally, Vijay N.; Hutchison, Dylan D.
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Abstract
Julia is a new language for writing data analysis programs that are easy to implement and run at high performance. Similarly, the Dynamic Distributed Dimensional Data Model (D4M) aims to clarify data analysis operations while retaining strong performance. D4M accomplishes these goals through a composable, unified data model on associative arrays. In this work, we present an implementation of D4M in Julia and describe how it enables and facilitates data analysis. Several experiments showcase scalable performance in our new Julia version as compared to the original Matlab implementation.
Date issued
2016-12
URI
http://hdl.handle.net/1721.1/115967
Department
Lincoln Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Department of Mathematics; Massachusetts Institute of Technology. Department of Mechanical Engineering
Journal
2016 IEEE High Performance Extreme Computing Conference (HPEC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Chen, Alexander, Alan Edelman, Jeremy Kepner, Vijay Gadepally, and Dylan Hutchison. “Julia Implementation of the Dynamic Distributed Dimensional Data Model.” 2016 IEEE High Performance Extreme Computing Conference (HPEC) (September 2016).
Version: Author's final manuscript
ISBN
978-1-5090-3525-0
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