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DTSTART;TZID=America/Chicago:20181114T140000
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UID:submissions.supercomputing.org_SC18_sess276_exforum123@linklings.com
SUMMARY:Data Protection Solutions for ML/AI
DESCRIPTION:Allison Armstrong and David Clements (Igneous Systems Inc)\n\n
 Igneous has customers building artificial intelligence models that revolut
 ionize the diagnosis and treatment of cancer and other life-threatening di
 seases. Their machine learning workflows utilize a proprietary storage sol
 ution as an archive tier, working in conjunction with high performance sto
 rage and computing. \n\nIgneous acts as the central repository for petabyt
 es of imaging data. Small subsets of data (< 2% of the entire dataset) are
  active at any one time for high performance compute, which acts as a “hot
  edge” for the data to be processed by image processing software running o
 n a high-performance deep learning platform. In addition, Igneous acts as 
 the central repository to archive all computational results, enabling the 
 “hot edge” to be cleared for subsequent workloads. Delivered as-a-Service 
 and remotely managed, Igneous enables organizations to keep their IT depar
 tments lean so that they can focus on groundbreaking research instead.\n\n
 Tag: Data Management, Machine Learning, Containers\n\nSession Chair: Prest
 on Smith (Purdue University)\n\n
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