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DTSTART;TZID=America/Denver:20231114T100000
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UID:submissions.supercomputing.org_SC23_sess291_rpost176@linklings.com
SUMMARY:Geospatial Filter and Refine Computations on NVIDIA Bluefield Data
  Processing Units (DPU)
DESCRIPTION:Derda Kaymak (Marquette University) and Satish Puri (Missouri 
 University of Science and Technology)\n\nIn this poster, we will show how 
 to leverage Nvidia's Bluefield Data Processing Unit (DPU) in geospatial sy
 stems. Existing work in literature has explored DPUs in the context of mac
 hine learning, compression and MPI acceleration. We show our designs on ho
 w to integrate DPUs into existing high performance geospatial systems like
  MPI-GIS. The workflow of a typical spatial computing workload consists of
  two phases - filter and refine. First we used DPU as a target to offload 
 spatial computations from the host CPU. We show the performance improvemen
 ts due to offload. Next we used DPU for network I/O processing. In network
  I/O case, the query data first comes to DPU for filtering and then the qu
 ery goes to CPU for refinement. DPU-based filter and refine system can be 
 useful in other domains like Physics where an FPGA is used to perform the 
 filter to handle Big Data.\n\nTag: Artificial Intelligence/Machine Learnin
 g, Architecture and Networks, Heterogeneous Computing, I/O and File System
 s, Performance Measurement, Modeling, and Tools, Post-Moore Computing, Pro
 gramming Frameworks and System Software, Quantum Computing\n\nRegistration
  Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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