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"Supercharge analytics over large IoT data: an OS approach"

Event Type
Lecture
Sponsor
CSL
Location
239 Coordinated Science Lab
Date
May 6, 2019   2:30 pm  
Speaker
Felix Xiaozhu Lin, Purdue University
Views
6
Originating Calendar
CSL General Event Calendar

This talk overviews our inquiry in systems software for taming large IoT data. I will describe two systems that target two complementary analytics paradigms: a data engine for processing large telemetry streams (hot data); a data store for querying large archival videos (cold data). The two systems exploit emerging hardware (e.g. 3D-stacked DRAM) as well as emerging workloads (e.g. neural networks). Both systems advance the state-of-the-art performance by orders of magnitude.

 

Our experiences highlight the significance of designing OSes for specific scenarios, where the OSes play key roles: mapping AI to new hardware, dynamically configuring AI, and trading off among competing objectives.

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