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DTSTAMP:20200129T163601Z
LOCATION:601
DTSTART;TZID=America/Denver:20191118T105500
DTEND;TZID=America/Denver:20191118T112000
UID:submissions.supercomputing.org_SC19_sess121_ws_pdsw109@linklings.com
SUMMARY:Enabling Transparent Asynchronous I/O Using Background Threads
DESCRIPTION:Workshop\n\nEnabling Transparent Asynchronous I/O Using Backgr
 ound Threads\n\nTang, Koziol, Byna, Mainzer, Li\n\nWith scientific applica
 tions moving toward exascale levels, an increasing amount of data is being
  produced and analyzed. Providing efficient data access is crucial to the 
 productivity of the scientific discovery process. Compared to improvements
  in CPU and network speeds, I/O performance lags far behind, such that mov
 ing data across the storage hierarchy can take longer than data generation
  or analysis. To alleviate this I/O bottleneck, asynchronous read and writ
 e operations have been provided by the POSIX and MPI-I/O interfaces and ca
 n overlap I/O operations with computation, and thus hide I/O latency. Howe
 ver, these standards lack support for non-data operations such as file ope
 n, stat, and close, and their read and write operations require users to b
 oth manually manage data dependencies and use low-level byte offsets. This
  requires significant effort and expertise for applications to utilize.\n\
 nTo overcome these issues, we present an asynchronous I/O framework that p
 rovides support for all I/O operations and manages data dependencies trans
 parently and automatically. Our prototype asynchronous I/O implementation 
 as an HDF5 VOL connector demonstrates the effectiveness of hiding the I/O 
 cost from the application with a low overhead and easy-to-use programming 
 interface.\n\nTag: Workshop Reg Pass, Big Data, Data Analytics, Data Manag
 ement, Storage\n\nRegistration Category: Workshop Reg Pass, Big Data, Data
  Analytics, Data Management, Storage
URL:https://sc19.supercomputing.org/presentation/?id=ws_pdsw109&sess=sess1
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