Mapping and Reducing the Brain on the Cloud
Esha Sahai, Tuhin Sahai

TL;DR
This paper demonstrates how cloud computing platforms like Amazon EC2 can be used to simulate large-scale neural networks using MapReduce, enabling scalable scientific computation with commodity hardware.
Contribution
It introduces a novel approach of modeling interconnected cortical neurons on cloud infrastructure using Hadoop and MapReduce, showcasing scalability for brain simulations.
Findings
Successful simulation of 1000 cortical neurons on Hadoop
Demonstrated feasibility of large-scale neural modeling on cloud platforms
Provided performance insights for cloud-based neural simulations
Abstract
The emergence of cloud computing has enabled an incredible growth in available hardware resources at very low costs. These resources are being increasingly utilized by corporations for scalable analysis of "big data" problems. In this work, we explore the possibility of using commodity hardware such as Amazon EC2 for performing large scale scientific computation. In particular, we simulate interconnected cortical neurons using MapReduce. We build and model a network of 1000 spiking cortical neurons in Hadoop, an opensource implementation of MapReduce, and present results.
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Taxonomy
TopicsFunctional Brain Connectivity Studies · Advanced Memory and Neural Computing · EEG and Brain-Computer Interfaces
