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UID:submissions.supercomputing.org_SC24_sess533_post114@linklings.com
SUMMARY:Performance Engineering and Mesoscale-Microscale Coupling for Wind
  Energy Simulations
DESCRIPTION:Mukul Dave, Ann Almgren, Donald Willcox, Weiqun Zhang, and Aar
 on Lattanzi (Lawrence Berkeley National Laboratory (LBNL))\n\nWind farm si
 mulations require data from mesoscale atmospheric simulations as initial a
 nd boundary conditions for the microscale turbine environments. The Energy
  Research and Forecasting (ERF) code bridges this scale gap and provides a
 n efficient GPU-enabled parallel implementation with adaptive mesh refinem
 ent through the underlying AMReX framework. This poster outlines strategie
 s that reduce the communication overhead among parallel processes through 
 run time settings or systemic changes in the memory management. This inclu
 des using shared-memory parallelism over CPUs, enabling direct GPU-GPU dat
 a transfers, and implementing a separate memory pool on the GPU for commun
 ication buffers. I will present the performance scaling and improvements f
 rom these techniques as part of the poster. We are currently developing an
  in-memory coupling of the compressible flow ERF code with the incompressi
 ble turbine solver ExaWind, which will allow holistic wind farm simulation
 s.\n\nRegistration Category: Tech Program Reg Pass, Exhibits Reg Pass\n\nS
 ession Chairs: Ayesha Afzal (Friedrich-Alexander University, Erlangen-Nure
 mberg; Erlangen National High Performance Computing Center); Sally Ellings
 on (University of Kentucky); and Alan Sussman (University of Maryland)\n\n
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