may 5 2021 UNM CS colloquium

content/talk/20210505_unm_cs/index.md

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+---
+title: Adding Fast GPU Derived Datatype Handing to Existing MPIs
+
+date: "2021-05-05T00:00:00Z"
+
+tags: [mpi]
+---
+
+*May 5th, 2:00 PM, University of New Mexico, Albuquerque, NM*
+
+Invited talk to the Computer Science Department Colloquium
+
+### Abstract
+
+MPI derived datatypes are an abstraction that simplifies handling of non-contiguous data in MPI applications.
+These datatypes are recursively constructed at runtime from primitive Named Types defined in the MPI standard.
+More recently, the development and deployment of CUDA-aware MPI implementations has encouraged the transition of distributed high-performance MPI codes to use GPUs.
+Such implementations allow MPI functions to directly operate on GPU buffers, easing integration of GPU compute into MPI codes.
+This talk presents a novel datatype handling strategy for nested strided datatypes on GPUs, and its evaluation on a leadership-class supercomputer that does not have built-in support for such datatypes.
+It focuses on the datatype strategy itself, implementation decisions based off measured system performance, and a technique for experimental modifications to closed software systems.
+
+### Link
+
+* [slides](/pdf/20210505_unm_slides.pdf)
+* [github](https://github.com/cwpearson/tempi)