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COST of Graph Processing Using Actors | | Ronak Buch
; | | Date: |
4 Jan 2023 | | Abstract: | Graph processing is an increasingly important domain of computer science,
with applications in data and network analysis, among others. Target graphs in
these applications are often large, leading to the creation of "big data"
systems designed to provide the scalability needed to analyze these graphs
using parallel processing. However, researchers have shown that while these
systems often provide scalability, they also often introduce overheads that
exceed the benefits they provide, sometimes lower absolute performance than
even simple serial implementations. This report studies the viability and
performance of actor model to implement scalable concurrent programs to perform
common graph computations. We show that relatively simple actor-based
implementations outperform both dedicated graph processing systems and the
benchmark serial implementations. | | Source: | arXiv, 2301.01395 | | Services: | Forum | Review | PDF | Favorites | |
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