Abstract
We demonstrate PrismX (PRAM with SSDs as Memory eXtension), a single-machine system for graph analytics. PrismX allows users to make practical use of existing PRAM algorithms without any change. To cope with the limited DRAM capacity, it employs NVMe SSDs as memory extension. Leveraging graph preprocessing, PrismX implements a series of system optimization strategies, which automatically and transparently adapt to the runtime workload, no matter whether the computation is CPU-bound or I/O-bound. We demonstrate PrismX for its (1) ease of programming by reusing PRAM algorithms, (2) efficiency by comparing with the state-of-the-art graph systems, single-machine or multi-machine, in-memory or out-of-core; (3) parallel scalability of in-memory PRAM algorithms, reducing runtime when more CPU cores are available; and (4) applications in credit risk assessment.
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