Parallelization of the algorithm WHAM with NVIDIA CUDA.

The aim of my thesis is to parallelize the Weighting Histogram Analysis Method (WHAM), which is a popular algorithm used to calculate the Free Energy of a molucular system in Molecular Dynamics simulations. WHAM works in post processing in cooperation with another algorithm called Umbrella Sampling. Umbrella Sampling has the purpose to add a biasing in the potential energy of the system in order to force the system to sample a specific region in the configurational space. Several N independent simulations are performed in order to sample all the region of interest. Subsequently, the WHAM algorithm is used to estimate the original system energy starting from the N atomic trajectories. The parallelization of WHAM has been performed through CUDA, a language that allows to work in GPUs of NVIDIA graphic cards, which have a parallel achitecture. The parallel implementation may sensibly speed up the WHAM execution compared to previous serial CPU imlementations. However, the WHAM CPU code presents some temporal criticalities to very high numbers of interactions. The algorithm has been written in C++ and executed in UNIX systems provided with NVIDIA graphic cards. The results were satisfying obtaining an increase of performances when the model was executed on graphics cards with compute capability greater. Nonetheless, the GPUs used to test the algorithm is quite old and not designated for scientific calculations. It is likely that a further performance increase will be obtained if the algorithm would be executed in clusters of GPU at high level of computational efficiency. The thesis is organized in the following way: I will first describe the mathematical formulation of Umbrella Sampling and WHAM algorithm with their apllications in the study of ionic channels and in Molecular Docking (Chapter 1); then, I will present the CUDA architectures used to implement the model (Chapter 2); and finally, the results obtained on model systems will be presented (Chapter 3).

Dielectrophoresis (dep) and electrowetting (ewod) as an anti-fouling process for antibacterial surfaces

Nowadays the medical field is struggling to decrease bacteria biofilm formation which leads to infection. Biomedical devices sterilization has not changed over a long period of time. This results in high costs for hospitals healthcare managements. The objective of this project is to investigate electric field effects and surface energy manipulation as solutions for preventing bacteria biofilm for future devices. Based on electrokinectic environments 2 different methods were tested: feasibility of electric gradient through mediums (DEP) reinforced by numerical simulations; and EWOD by the fabrication of golden interdigitated electrodes on silicon glass substrates, standard ~480 nm Teflon (PTFE) layer and polymeric gasket to contain the bacteria medium. In the first experiment quantitative analysis was carried out to achieve forces required to reject bacteria without considering dielectric environment limitations as bacteria and medium frequency dependence. In the second experiment applied voltages was characterized by droplets contact angle measurements and put to the live bacteria tests. The project resulted on promising results for DEP application due to its wide range of frequency that can be used to make a “general” bacteria rejecting; but in terms of practicality, EWOD probably have higher potential for success but more experiments are needed to verify if can prevent biofilm adhesion besides the Teflon non-adhesive properties (including limitations as Teflon breakthrough, layer sensitivity) at incubation times larger than 24 hours.