Speaker: Holger Pirk

He / him / his

Associate Professor for Data Management Systems at Imperial College London and Avid Runner — Minimizing Cache Misses, Thread Divergence and Aerobic Decoupling

Holger Pirk is an Associate Professor in the Large‑Scale Data and Systems group at Imperial College London and an avid runner. His research spans all things data: analytics, transactions, systems, algorithms, data structures, processing models, and everything in between. While some of his work targets “traditional” relational databases, his broader aim is to expand the applicability of data management techniques. To this end, Holger studies Composable Database Systems—systems that are extensible to support heterogeneous workloads, data models, and hardware. This naturally leads to research at the intersection of data management, compilers, and computer architecture, with applications in areas ranging from generative modeling and graph processing to classic analytical workloads. Before joining Imperial, Holger was a Postdoctoral Associate in the Database Group at MIT CSAIL, a PhD student in the Database Architectures Group at CWI in Amsterdam, and an undergraduate in Computer Science at Humboldt‑Universität zu Berlin. Holger knows how to speak and write, as evidenced, respectively, by a CIDR Gong Show Award and a VLDB Best Paper Award.

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Session

Looking Under the Hood: Data Processing Systems Performance Tricks (and How to Apply Them to Your Code)

Modern data processing systems—databases, analytics engines, vector stores, and stream processors—hide an extraordinary amount of performance engineering beneath their abstractions.

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Date

Wednesday Mar 18 / 02:45PM GMT ( 50 minutes )

Location

Mountbatten (6th Fl.)

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