Demonstrator for HEP event-processing framework in Julia: performance perspective

Event-processing frameworks are an important part of High Energy Physics (HEP) software, providing the infrastructure for a wide range of domain-specific tasks such as event reconstruction and simulation. They are designed to deliver high throughput and meet the demanding performance requirements of the field. A key component of modern frameworks is the scheduler, which enables efficient parallelization of complex data processing workflows. The Julia programming language, with its focus on high performance and a growing ecosystem for scientific computing, presents an interesting option for implementing such frameworks. In this work, we focus on the performance of demonstrator project for an event-processing framework developed in Julia and using Dagger.jl, a library for parallel and heterogeneous processing. We specifically evaluate its multithreaded performance and scalability. The discussion will highlight both the advantages and challenges of using Dagger and Julia for this type of HEP application, providing insights into their potential for future event-processing frameworks.

Institutions

Publication Details

Published
2025-07-30
DOI
https://doi.org/10.17181/x7n0h-5rr63
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Demonstrator for HEP event-processing framework in Julia: performance perspective

Geochemistry and Geologic Mapping
article

Demonstrator for HEP event-processing framework in Julia: performance perspective

article en

Abstract

Event-processing frameworks are an important part of High Energy Physics (HEP) software, providing the infrastructure for a wide range of domain-specific tasks such as event reconstruction and simulation. They are designed to deliver high throughput and meet the demanding performance requirements of the field. A key component of modern frameworks is the scheduler, which enables efficient parallelization of complex data processing workflows. The Julia programming language, with its focus on high performance and a growing ecosystem for scientific computing, presents an interesting option for implementing such frameworks. In this work, we focus on the performance of demonstrator project for an event-processing framework developed in Julia and using Dagger.jl, a library for parallel and heterogeneous processing. We specifically evaluate its multithreaded performance and scalability. The discussion will highlight both the advantages and challenges of using Dagger and Julia for this type of HEP application, providing insights into their potential for future event-processing frameworks.

ETH Zurich (CH), Ukrainian Catholic University (UA), European Organization for Nuclear Research (CH)
Industry, innovation and infrastructure
Openalex Percentile: Top 35%
Geochemistry and Geologic Mapping
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Demonstrator for HEP event-processing framework in Julia: performance perspective · (2025) | TGRS Research Map | TGRS