Vignesh Srinivasakumar, Muthumanikandan Vanamoorthy, Siddarth Sairaj, S. Ganesh
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An alternative C++-based HPC system for Hadoop MapReduce
Abstract MapReduce (MR) is a technique used to improve distributed data processing vastly and can massively speed up computation. Hadoop and MR rely on memory-intensive JVM and Java. A MR framework based on High-Performance Computing (HPC) could be used, which is both memory-efficient and faster than standard MR. This article explores a C++-based approach to MR and its feasibility on multiple factors like developer friendliness, deployment interface, efficiency, and scalability. This article also introduces Eager Reduction and Delayed Reduction techniques to speed up MR.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.