The first part of this work reviews the algebraic matricial approach to transport data inversion. It works for the convection-diffusion transport equation used for periodic signals and provides a formally exact solution, as well as a quantitative assessment of error bars. The standard methods of reconstruction infer the diffusivity D and pinch V by matching experimental data against those simulated by transport codes. These methods do not warrant the validity of either the underlying models of transport, or of the reconstructed D(r) and V(r), even when the results look reasonable.

One of the most formidable challenges in modern biology is to get a unified view of the various mechanisms governing the behavior and of the causal relationships among different parts of a living system. It is coming clearer nowadays that to get such comprehensive picture computational models embracing different observation levels in space and time have to be formulated to explain the enormous amount of data deriving from -omic high throughput measurements methods.

We analyze a peer-assisted Video-on-Demand (VoD) system in which users contribute their upload bandwidth to the redistribution of a video that they are downloading or that they have cached locally. Our target is to characterize the additional bandwidth that servers must supply to immediately satisfy all requests to watch a given video. We develop an approximate fluid model to compute the required server bandwidth in the sequential delivery case, as well as in controlled nonsequential swarms.

We describe a solution for fast indexing and searching within large heterogeneous data sets whose main purpose is to support investigators that need to analyze forensic disk images originated by seizures or created from bodies of evidence. Our approach is based on a combination of techniques aimed at improving efficiency and reliability of the indexing process.We do not rely on existing frameworks like Hadoop but borrow concepts from different contexts including High Performance Computing and Database management.

We present and compare the performances of two many-core architectures: the Nvidia Kepler and the Intel MIC both in a single system and in cluster configuration for the simulation of spin systems. As a benchmark we consider the time required to update a single spin of the 3D Heisenberg spin glass model by using the Over-relaxation algorithm. We present data also for a traditional high-end multi-core architecture: the Intel Sandy Bridge.