  This work presents a comprehensive performance analysis and optimization of a
multiscale agent-based cellular simulation. The optimizations applied are
guided by detailed performance analysis and include memory management, load
balance, and a locality-aware parallelization. The outcome of this paper is not
only the speedup of 2.4x achieved by the optimized version with respect to the
original PhysiCell code, but also the lessons learned and best practices when
developing parallel HPC codes to obtain efficient and highly performant
applications, especially in the computational biology field.
