Outsourced computing is increasingly popular thanks to the effectiveness and convenience of cloud computing *-as-a-Service offerings. However, cloud nodes can potentially misbehave in order to save resources. As such, some guarantee over the correctness and availability of results is needed. Exploiting the redundancy of cloud nodes can be of help, even though smart cheating strategies render the detection and correction of fake results much harder to achieve in practice.

In this paper we deal with high oscillatory systems and numerical methods for the approximation of their solutions. Some classical schemes developed in the literature are recalled and a recent approach based on the expression of the oscillatory solution by means of the exponential map is considered. Moreover we introduce a new method based on the Cayley map and provide some numerical tests in order to compare the different approaches

Premixed combustion modes in compression ignition engines are studied as a promising solution to meet fuel economy and increasingly stringent emissions regulations. Nevertheless, PCCI combustion systems are not yet consolidated enough for practical applications. The high complexity of such combustion systems in terms of both air-fuel charge preparation and combustion process control requires the employment of robust and reliable numerical tools to provide adequate comprehension of the phenomena.

A hydro-kinetic scheme for water-like fluids, based on a lattice version of the Boltzmann equation, is presented and applied to the popular TIP3P model of liquid water. By proceeding in much larger steps than molecular dynamics, the scheme proves to be very effective in attaining global minima of classical pair potentials with directional and radial interactions, as confirmed by further simulations using the three-dimensional Ben-Naim water potential.

A method to derive accurate spatially dense maps of 3-D terrain displacement velocity is presented. It is based on the merging of terrain displacement velocities estimated by time series of interferometric synthetic aperture radar (InSAR) data acquired along ascending and descending orbits and repeated GPS measurements. The method uses selected persistent scatterers (PSs) and GPS measurements of the horizontal velocity. An important step of the proposed method is the mitigation of the impact of atmospheric phase delay in InSAR data.

Direct numerical approximation of a continuous-time infinite horizon control problem, requires to recast the model as a discrete-time, finite-horizon control model. The quality of the optimization results can be heavily degraded if the discretization process does not take into account features of the original model to be preserved.

A model is proposed to describe the spike-frequency adaptation observed in many neuronal systems. We assume that adaptation is mainly due to a calcium-activated potassium current, and we consider two coupled stochastic differential equations for which an analytical approach combined with simulation techniques and numerical methods allow to obtain both qualitative and quantitative results about asymptotic mean firing rate, mean calcium concentration and the firing probability density. A related algorithm, based on the Hazard Rate Method, is also devised and described.

Graphics processing units (GPUs) are increasingly common on desktops, servers, and embedded platforms. In this article, we report on new security issues related to CUDA, which is the most widespread platform for GPU computing. In particular, details and proofs-of-concept are provided about novel vulnerabilities to which CUDA architectures are subject. We show how such vulnerabilities can be exploited to cause severe information leakage. As a case study, we experimentally show how to exploit one of these vulnerabilities on a GPU implementation of the AES encryption algorithm.

Graphics processing units (GPU) are currently used as a cost-effective platform forcomputer simulations and big-data processing. Large scale applications require thatmultiple GPUs work together but the efficiency obtained with cluster of GPUs is, at times,sub-optimal because the GPU features are not exploited at their best. We describe how itis possible to achieve an excellent efficiency for applications in statistical mechanics,particle dynamics and networks analysis by using suitable memory access patterns andmechanisms like CUDA streams, profiling tools, etc.