Track host
About the track
Explore contemporary techniques for maximizing application speed, covering everything from compiler optimization and efficient concurrency to advanced profiling tools and front-end rendering performance.
Sessions in this track
Wednesday 18 March. 5 sessions per track, chosen and introduced by the Track Host.
10:35 Windsor (5th Fl.) Session AI/ML Machine Learning at the Edge of Scale and Speed: Nanosecond Inference at the CERN Large Hadron Collider Thea Klaeboe Aarrestad Particle Physics and Real-Time ML @CERN @ETH Zürich 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. 11:45 Windsor (5th Fl.) Session Data Systems Vector Search on Columnar Storage Peter Boncz Professor @CWI, Co-Creator of MonetDB, VectorWise and MotherDuck, Database Systems Researcher, and Entrepreneur Managing vector data entails storing, updating, and searching collections of large and multi-dimensional pieces of data. Some believe that this justifies the creation of a new class of data systems specialized for this. 13:35 Mountbatten (6th Fl.) Session architecture Not Just I/O: Using Async/Await for Computational Scheduling Orson Peters Senior Engineer of Query Execution @Polars, (Co-)Author of Stdlib Sort in Rust & Go In the past two years I have developed a new query execution engine for Polars, which not only tries to execute as much of your query in parallel as possible, but in a streaming fashion as well, such that you can process data sets which do not fit in memory. 14:45 Mountbatten (6th Fl.) Session Data Management Looking Under the Hood: Data Processing Systems Performance Tricks (and How to Apply Them to Your Code) Holger Pirk Associate Professor for Data Management Systems at Imperial College London and Avid Runner — Minimizing Cache Misses, Thread Divergence and Aerobic Decoupling Modern data processing systems—databases, analytics engines, vector stores, and stream processors—hide an extraordinary amount of performance engineering beneath their abstractions. 15:55 Windsor (5th Fl.) Session compilers Automatically Retrofitting JIT Compilers Laurence Tratt Shopify / Royal Academy of Engineering Research Chair in Language Engineering @King's College London We as a community have attempted, multiple times, to speed up languages such as Lua, Python, and Ruby by hand-writing JIT compilers. Sometimes we've had short-term success, but the size, and pace of change, of their standard implementations has proven difficult to keep up with over time.
76%
senior dev or higher
1:11
speaker ratio
60+
practitioners
QCon London 2026 is a three day conference for senior software engineers, architects and team leads. An international program committee of working engineers selects every session. Patterns and practices, not products and pitches.