systems
Looking Under the Hood: Data Processing Systems Performance Tricks (and How to Apply Them to Your Code)
Wednesday Mar 18 / 02:45PM GMT
Modern data processing systems—databases, analytics engines, vector stores, and stream processors—hide an extraordinary amount of performance engineering beneath their abstractions.
Holger Pirk
Associate Professor for Data Management Systems at Imperial College London and Avid Runner — Minimizing Cache Misses, Thread Divergence and Aerobic Decoupling
Machine Learning at the Edge of Scale and Speed: Nanosecond Inference at the CERN Large Hadron Collider
Wednesday Mar 18 / 10:35AM GMT
The CERN Large Hadron Collider (LHC) produces O(10,000) exabytes of raw data annually from high-energy proton collisions. Handling this volume under strict compute and storage limits requires real-time event filtering capable of processing millions of collisions per second.
Thea Klaeboe Aarrestad
Particle Physics and Real-Time ML @CERN @ETH Zürich