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UoA ACM Student Chapter

Title — JIT works: embracing heterogeneity for scalable data analytics Abstract — In today’s ever-growing demand for fast data analytics, heterogeneity severely undermines performance. On one hand, data format variety forces people to load their data into a single format, spending tons of resources and often losing valuable structural information. Or, requires a separate database system for each data type plus an integration tool to bring all the results together. All options are costly and waste valuable resources. On the other hand, “franken-chips” equipped with different types of potent compute units are severely under-utilised when running data analytics, as we’re used to coding with a CPU in mind and other core types are employed opportunistically, as an accelerating luxury. Nevertheless, hardware roadmaps indicate increasing levels of compute heterogeneity, and accelerator-level parallelism (ALP) is indeed the new way to make the best out of any hardware platform. Writing fast as well as programs that are portable to all kinds of microarchitectures, however, is an unsolved tradeoff. I will show how just-in-time (JIT) data virtualisation and code generation technologies can help execute queries fast across all kinds of data without costly preparation or heavy installations, as well as enable excellent utilisation of different hardware devices. Bio — Anastasia Ailamaki is a Professor of Computer and Communication Sciences at EPFL and the CEO and co-founder of RAW Labs SA, a Swiss company that develops enables digital transformation for entreprises through real-time analysis of heterogeneous big data. Previously, she was on the faculty of the Computer Science Department at CMU, where she held the Finmeccanica endowed chair. She has received the 2019 ACM SIGMOD Edgar F. Codd Innovations Award, the 2019 EDBT Test of Time award, the 2018 Nemitsas Prize in Computer Science, an ERC Consolidator Award (2013), the European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), and ten best-paper awards in database, storage, and computer architecture conferences. She is an ACM fellow, an IEEE fellow, and an elected member of the Swiss, the Belgian, and the Cypriot National Research Councils.

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