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DTSTAMP:20240116T191702Z
LOCATION:DEF Concourse
DTSTART;TZID=America/Denver:20231114T100000
DTEND;TZID=America/Denver:20231114T170000
UID:submissions.supercomputing.org_SC23_sess291_rpost176@linklings.com
SUMMARY:Geospatial Filter and Refine Computations on NVIDIA Bluefield Data
  Processing Units (DPU)
DESCRIPTION:Posters, Research Posters\n\nDerda Kaymak (Marquette Universit
 y) and Satish Puri (Missouri University of Science and Technology)\n\nIn t
 his poster, we will show how to leverage Nvidia's Bluefield Data Processin
 g Unit (DPU) in geospatial systems. Existing work in literature has explor
 ed DPUs in the context of machine learning, compression and MPI accelerati
 on. We show our designs on how to integrate DPUs into existing high perfor
 mance geospatial systems like MPI-GIS. The workflow of a typical spatial c
 omputing workload consists of two phases - filter and refine. First we use
 d DPU as a target to offload spatial computations from the host CPU. We sh
 ow the performance improvements due to offload. Next we used DPU for netwo
 rk I/O processing. In network I/O case, the query data first comes to DPU 
 for filtering and then the query goes to CPU for refinement. DPU-based fil
 ter 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\nRegistration Ca
 tegory: Tech Program Reg Pass, Exhibits Reg Pass
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