  The simulation of the behavior of the human brain is one of the most
ambitious challenges today with a non-end of important applications. We can
find many different initiatives in the USA, Europe and Japan which attempt to
achieve such a challenging target. In this work, we focus on the most important
European initiative (the Human Brain Project) and on one of the models
developed in this project. This tool simulates the spikes triggered in a neural
network by computing the voltage capacitance on the neurons' morphology, being
one of the most precise simulators today. In the present work, we have
evaluated the use of MPI+OpenMP tasking on top of this framework. We prove that
this approach is able to achieve a good scaling even when computing a
relatively low workload (number of neurons) per node. One of our targets
consists of achieving not only a highly scalable implementation, but also to
develop a tool with a high degree of abstraction without losing control and
performance by using \emph{MPI+OpenMP} tasking. The main motivation of this
work is the evaluation of this cutting-edge simulation on multi-morphology
neural networks. The simulation of a high number of neurons, which are
completely different among them, is an important challenge. In fact, in the
multi-morphology simulations, we find an important unbalancing between the
nodes, mainly due to the differences in the neurons, which causes an important
under-utilization of the available resources. In this work, the authors present
and evaluate mechanisms to deal with this and reduce the time of this kind of
simulations considerably.
