The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop: ISAV23: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization
Authors: Kristi Belcher, David Beckingsale, Nicole Marsaglia, and Marty McFadden (Lawrence Livermore National Laboratory)
Abstract: Because memory is a highly constrained resource, Umpire, a data and memory management API, was created at Lawrence Livermore National Laboratory (LLNL). Umpire provides memory pools which enable less expensive ways to allocate very large amounts of memory in HPC environments. Additionally, memory pools can be used when many small allocations are needed to avoid expensive calls to the underlying device-specific API. In-situ visualization is inherently resource constrained, making Umpire’s memory management API a valuable tool for improving performance. Umpire is used in many simulation codes at LLNL that also rely on cutting-edge in-situ visualization libraries. This lightning talk discusses Umpire's advantages and use cases, including some examples of in-situ visualization applications which rely on Umpire to improve memory performance.