About
The Large Hadron Collider (LHC) at CERN has generated a vast amount of information from physics events, reaching peaks of TB of data per day. Many reports show that the current analysis models (and more generally, data processing interfaces) would not be able to efficiently accommodate the amount of data in the next few years. It is both the responsibility of the frameworks to provide efficient computing tools and the user's responsibility to optimally exploit these resources. The latter is of particular interest in this lecture.
The purpose of this talk is to familiarize students with mechanisms to efficiently profile the performance of C++ and Python applications, going through real-world HEP analysis. The core of the lecture will be the identification of hotspots via `perf` and techniques for mitigation of different kinds of bottlenecks..
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The talk
Credits and licence
- Institution
- CERN
- Department
- Inverted CSC
- Speaker
- Ivan Kabadzhov
- Year
- 2023
- Language
- English
- Subjects
- Computer science
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed