As a matter of fact, when several batches of simulations need to be executed, the necessary computing power can rapidly overtake the capabilities of standard desktop computers, therefore requiring high-performance computing solutions.
In these fields, the use of high-performance computing solutions is motivated by the need of performing large numbers of in silico analysis to study the behavior of biological systems in different conditions, which necessitate a computing power that usually overtakes the capability of standard desktop computers.
Recent developments in the area of Graphic Processing Units (GPUs) make it possible to have access to high-performance computing solutions at a low cost, allowing their use in many scientific problems.
The aim of this special issue is to present the latest advances in the field of omics data processing with high-performance computing solutions and big data analysis paradigms, showing the potential repercussions of these technologies in translational medicine.
A clear awareness of present high performance computing (HPC) solutions in bioinformatics, Big Data analysis paradigms for computational biology, and the issues that are still open in the biomedical and healthcare fields represent the starting point to win this challenge.
Therefore, for the advance of computing science, it is important that High Performance Computing (HPC) techniques and solutions be proposed and studied.
Among the public cloud providers, Amazon EC2 provides suitable solutions for high performance computing applications, so we analyzed its pricing models (http://aws.amazon.com/ec2/pricing/) for their adoption in our simulation.
Scientific visualization, numerical solution methods, high performance computing.
We present a solution from high performance computing, which splits the problem up and computes it in parallel on a distributed memory system.
Such intense computation requires high performance computing.
