Computational challenges in modeling and simulating living matter

Computational modeling has been successfully used to help scientists understand physical and biological phenomena. Recent technological advances allowthe simulation of larger systems, with greater accuracy. However, devising those systems requires new approaches and novel architectures, such as the use of parallel programming, so that the application can run in the new high performance environments, which are often computer clusters composed of different computation devices, as traditional CPUs, GPGPUs, Xeon Phis and even FPGAs. It is expected that scientists take advantage of the increasing computational power to model and simulate more complex structures and even merge different models into larger and more extensive ones. This paper aims at discussing the challenges of using those devices to simulate such complex systems.