Innovative Algorithms

Algorithms to perform the real-time processing in the trigger and the reconstruction of both real and simulated detector data are critical components of HEP’s computing challenge. These algorithms face a number of new challenges in the next decade due to new and upgraded accelerator facilities, detector upgrades and new detector technologies, increases in anticipated event rates, and emerging computing architectures. Projects in the IA area are focused in three areas:

• Developing tracking algorithms for the HL-LHC
• Re-engineering algorithms for hardware accelerators
• Exploiting major advances in machine learning

Tracking for the HL-LHC is an area in particular need of novel approaches as it is expected to require a large fraction of the CPU budget. IA is working to develop more efficient and performant tracking algorithms. Hardware accelerators are expected to be the way forward to speed up reduce infrastructure cost. IA is exploring the use of hardware accelerators for tracking and the use of ML on accelerators in realistic HEP applications. In the area of machine learning, IA aims to capitalize on industry and data science techniques and tools. In particular, we are investigating new HEP applications of ML and to apply new ML techniques to HEP.

Contact us: ia-team@iris-hep.org