Presentation
Towards Disaggregated NDP Architectures for Large-scale Graph Analytics
DescriptionThe performance of large-scale graph analytics is limited by the capacity and performance of the memory subsystem on the platforms on which they execute. In this paper, we first discuss the limitations of existing approaches to scaling graph processing, and describe how they can be addressed via the use of disaggregated solutions with near-data processing (NDP) capabilities. Using observations from experimental analysis of the tradeoffs for different types of graphs and analytics kernels, we then identify the systems-level mechanisms that will be required by future graph analytics frameworks for disaggregated NDP architectures.