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Beyond X-Stream

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X-Stream is a system for processing large graphs on a single machine that was built at EPFL . X-Stream is capable of handing graphs about the size of all of Facebook on a single machine using secondary storage. X-Stream is also unique in being designed for processing graphs both from main memory and from secondary storage based on the observation for either of the two memory hierarchies sequential access to the slowest level is the best strategy. In the first part of the talk I will cover the design principles of X-Stream drawing a link between graph structure and X-Stream design principles illustrating why it works well. In the second part of the talk I will sketch out further work being done on the X-Stream project. This includes looking into how we can efficiently implement graph analytics on top of X-Stream’s edge-centric computation model and a scale-out successor of X-Stream with which we managed to process a terascale (1 trillion edges) graph on a tiny cluster (4×1U servers).

Bio: Amitabha Roy is a post-doctoral researcher in the Laboratory for Operating Systems at EPFL where he leads the X-Stream graph processing project and collaborates on the Orbe key-value store. He likes building systems that involve an intersection between algorithms, systems and computer architecture. Amitabha got his PhD from the Systems Research Group at the University of Cambridge where he built a transparent implementation of software transactional memory for x86 machine code. He has previously worked at Intel on the performance and correctness of memory subsystems including early exploratory work on Intel’s quick path interconnect.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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