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DTSTAMP:20190719T085743Z
LOCATION:HG F 3
DTSTART;TZID=Europe/Stockholm:20190612T130000
DTEND;TZID=Europe/Stockholm:20190612T133000
UID:submissions.pasc-conference.org_PASC19_sess117_msa272@linklings.com
SUMMARY:Introducing Big Data Technologies in the Analysis of Brain Region 
 Simulations at Large-Scale
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Physi
 cs, Life Sciences\n\nIntroducing Big Data Technologies in the Analysis of 
 Brain Region Simulations at Large-Scale\n\nPlanas, Schürmann\n\nThe simula
 tion of larger brain regions has been made possible in the past years than
 ks to the increasing computational power of computing systems. For example
 , while simulations involving up to a few thousands of neurons were possib
 le ten years ago, nowadays scientists can launch simulations of millions o
 r even billions of neurons. However, the capabilities in terms of data ana
 lysis and I/O-demanding applications have not increasing on par. This has 
 led the community to the research of alternative solutions, including big 
 data or artificial intelligence. In this talk, we will present how the ana
 lysis of large-scale simulations of brain regions can leverage from the us
 e of big data technologies, like Apache Spark. We will present the introdu
 ction of a framework that helps scientists accelerate their data analysis.
  In addition, we will see how this framework can be integrated into the ex
 isting tools. This last part is of relevant interest for scientists, as th
 ey can benefit from the latest, high-performance technologies without chan
 ging their usual data analysis software pipeline. Finally, we will present
  a performance evaluation to prove the validity of our work.
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