A Multi-purpose Framework for Efficient Parallelized Execution of Charged Particle Tracking

Abstract

Complex particle tracking software used in High Energy Physics experiments already pushes the edges of computing resources with demanding requirements for speed and memory throughput, but the future experiments pose an even greater challenge. Although many supercomputers already reached petascale capacities using many-core architectures and accelerators, many scientific applications still need to efficiently make use of the new resources. This research work is focused on investigating the parallelization potential of the particle reconstruction flow and ultimately, on developing a prototype of a framework which could contribute to a smooth transition to a platform-agnostic code base which avoids duplicating implementations for different architectures, while ensuring improved performance.