llnl / llnl/axom

Add a GPU-friendly hash map to Axom core

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#574 3 comments 1 reaction 1 assignee View on GitHub

@publixsubfan is already working on this.

Since Feb 13, 2023.

Core enhancement GPU Reviewed
Dominant language
C++
Stars
196
Forks
34
Avg merge
4d 1h
Merged PRs (30d)
11

Description

Hash maps already have an STL implementation. However, that STL implementation does not play nicely with accelerators, as most STL data structures don’t. This is unfortunate, due to the usefulness of the data structure, especially given the context that methods already exist in the literature for concurrent and GPU-targeted hash maps. This is a gap Axom can fill.

To support use of a hash map for applications such as physics simulations on GPU, Axom needs a hash map that works both on CPU and on supported accelerators. It will need to support access, insertion, and deletion on all supported platforms.

I’ll be implementing this through RAJA and Umpire, as Map in the Core module, starting with a sequential implementation, then moving into the others.

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