Speaker
Description
Julia has gained attention in high-energy physics (HEP) as a programming language that combines high-level expressiveness with competitive performance. This work explores its potential as a replacement for C++ in HEP applications, in particular in the context of trigger and reconstruction. The studies reported here include ahead-of-time compilation of jet reconstruction packages, a scheduling demonstrator for an event-processing framework, and a Julia port of the CMS Patatrack standalone pixel tracking.
While Julia offers attractive ergonomics, the studies revealed multiple limitations. Ahead-of-time compilation is still slower and produces significantly larger binaries than C++ alternatives, and residual just-in-time (JIT) compilation may persist in compiled binaries, limiting their suitability for latency-sensitive applications. Although Julia delivers good single-threaded performance for isolated tasks, significant scaling limitations in multi-threaded throughput were observed under frequent memory allocation due to its stop-the-world garbage collector. These issues arise from fundamental language design decisions rather than ecosystem immaturity and may pose significant challenges for adopting Julia in large-scale HEP code-bases or in latency-sensitive, highly parallel, high-throughput applications.