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Cloud computing / Cloud infrastructure / Hadoop / MapReduce / Apache Hadoop / Algorithmic skeleton / Map / Computer cluster / Cloudera / Computing / Concurrent computing / Parallel computing


Comparing Fork/Join and MapReduce Robert Stewart∗1 and Jeremy Singer†2 1 Mathematical and Computer Sciences, Heriot Watt University, Edinburgh 2
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Document Date: 2012-08-28 09:44:15


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Company

IBM / Computer Sciences / Oracle / Google / Intel / Microsoft / /

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Event

FDA Phase / /

Facility

Java fork/join library / Heriot Watt University / Java library / /

IndustryTerm

Search engine providers / hybrid processing models / parallel runtime systems / work stealing algorithm / throughput text mining applications / iterative and recursive algorithms / software frameworks / realistic implementation technologies / distributed-memory computing platforms / garbage collection algorithm / dynamic load-balancing systems / distributed computing fundamentals / conventional software / online repository5 / /

OperatingSystem

Unix / Fork / Linux / CentOS / /

Organization

School of Computing Science / Heriot Watt University / /

Person

Robert Stewart / Jeremy Singer / /

Position

driver / Singer / garbage collector / representative / General / MapReduce programmer / /

Product

MapReduce / SICSA / /

ProgrammingLanguage

Haskell / Perl / Cilk / Java / Erlang / C / Python / C++ / /

RadioStation

Watt / /

Technology

ethernet / garbage collection algorithm / load balancing / Java / Unix / Linux / realistic implementation technologies / work stealing algorithm / iterative and recursive algorithms / Search engine / Perl / /

URL

http /

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