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LOCATION:501-502
DTSTART;TZID=America/Denver:20231112T160600
DTEND;TZID=America/Denver:20231112T161600
UID:submissions.supercomputing.org_SC23_sess439_ws_worksa104@linklings.com
SUMMARY:Transcriptomics Atlas Pipeline:  Cloud vs HPC
DESCRIPTION:Piotr Kica (Sano Centre for Computational Medicine, Krakow, Po
 land; AGH University of Science and Technology, Krakow, Poland); Sabina Li
 chołai (Sano Centre for Computational Medicine, Krakow, Poland); and Macie
 j Malawski (Sano Centre for Computational Medicine, Krakow, Poland; AGH Un
 iversity of Science and Technology, Krakow, Poland)\n\nTranscriptomics stu
 dies the RNA present in a specific cell or tissue at a given time or condi
 tion. This dependence on time makes the problem computationally challengin
 g, as the data generated by transcriptomics experiments is larger than the
  genomics studies on DNA sequences. The goal of the Transcriptomics Atlas 
 project is to create a database of analyzed RNA sequences corresponding to
  given tissue and organ types based on the data from  public repositories 
 and make it available for researchers. We describe our transcriptomics atl
 as pipeline as an example of a new data- and compute-intensive scientific 
 workflow. After analyzing the requirements of the tasks in the pipeline, w
 e describe our proposed cloud architecture. We present the preliminary res
 ults of the experimental evaluation of the pipeline in the AWS cloud, and 
 compare the performance results to the traditional execution on the HPC cl
 uster.\n\nTag: Applications, Cloud Computing, Distributed Computing, Edge 
 Computing, Large Scale Systems\n\nRegistration Category: Workshop Reg Pass
 \n\nSession Chairs: Silvina Caino-Lores (National Institute for Research i
 n Digital Science and Technology (Inria)) and Anirban Mandal (Renaissance 
 Computing Institute (RENCI), University of North Carolina at Chapel Hill)\
 n\n
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