국내 최대 기계 및 로봇 연구정보

기술보고서

기술보고서 게시판 내용
타이틀	Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis
저자	Duffy, Daniel Q.;; Schnase, John L.;; Thompson, John H.;; Freeman, Shawn M.;; Clune, Thomas L.
Keyword	APPLICATIONS PROGRAMS (COMPUTERS); CLIMATE MODELS;; DATA REDUCTION;; DISTRIBUTED PROCESSING;; EFFICIENCY;; MATHEMATICAL MODELS;; PROTOTYPES;; SIMULATION
URL	http://hdl.handle.net/2060/20120009187
보고서번호	GSFC.CP.6024.2012
발행년도	2012
출처	NTRS (NASA Technical Report Server)
ABSTRACT	MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.