The paper presents structures and techniques aimed towards co-designing scalable asynchronous and decentralized dynamic graph processing for fine-grain memory-driven architectures. It uses asynchronous active messages, in the form of actions that send "work to data", with a programming and execution model that allows spawning tasks from within the data-parallelism combined with a data-structure that parallelizes vertex object across many scratchpad memory-coupled cores and yet provides a single programming abstraction to the data object.
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Chandio et al. (2024) studied this question.
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