Join us for an exciting talk on Maximus, a revolutionary modular query engine for data analytics on heterogeneous systems. Presented by Marko Kabić, a Ph.D. student from ETH Zurich System Group, this session will explore how Maximus harnesses the power of GPUs and CPUs to tackle the complexities of modern data processing.

Title: Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems

Speaker: Marko Kabić | ETH Zurich

Location: Online

Time: 05/07(Wed) 13:30-14:30 (UTC+01:00)London

External: https://app.huawei.com/wmeeting/join/95709180/ML6masIeHafOBZ9P8HZysSWGQt3RA4okX

Meeting ID: 95709180

Passcode:375969

Registration: https://www.smartsurvey.co.uk/s/3N8U7J/

Abstract:

Several trends are changing the underlying fabric for data processing in fundamental ways. On the hardware side, machines are becoming heterogeneous with smart NICs, TPUs, DPUs, etc., but specially with GPUs taking a more dominant role. On the software side, the diversity in workloads, data sources, and data formats has given rise to the notion of composable data processing where the data is processed across a variety of engines and platforms. Finally, on the infrastructure side, different storage types, disaggregated storage, disaggregated memory, networking, and interconnects are all rapidly evolving, which demands a degree of customization to optimize data movement well beyond established techniques. To tackle these challenges, in this paper, we present Maximus, a modular data processing engine that embraces heterogeneity from the ground up. Maximus can run queries on CPUs and GPUs, can split execution between CPUs and GPUs, import and export data in a variety of formats, interact with a wide range of query engines through Substrait, and efficiently manage the execution of complex data processing pipelines. Through the concept of operator-level integration, Maximus can use operators from third-party engines and achieve even better performance with these operators than when they are used with their native engines. The current version of Maximus supports all TPC-H queries on both the GPU and the CPU and optimizes the data movement and kernel execution between them, enabling the overlap of communication and computation to achieve performance comparable to that of the best systems available, but with a far higher degree of completeness and flexibility.

Bio:

I am a PhD student in Computer Science in the Systems Group at ETH Zurich (Switzerland), supervised by prof. Gustavo Alonso. During the studies, I did an internship at Hewlett-Packard Labs. Before commencing my PhD studies, I worked for several years at Swiss National Supercomputing Centre (CSCS). My research focuses on data management systems for data analytics on heterogeneous hardware.

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