Forest resampling for distributed sequential Monte Carlo

This paper brings explicit considerations of distributed computing architectures and data structures into the rigorous design of Sequential Monte Carlo (SMC) methods. A theoretical result established recently by the authors shows that adapting interaction between particles to suitably control the Effective Sample Size (ESS) is sufficient to guarantee stability of SMC algorithms. Our objective is to leverage this result and devise algorithms which are thus guaranteed to work well in a distributed setting. We make three main contributions to achieve this. Firstly, we study mathematical properties of the ESS as a function of matrices and graphs that parameterize the interaction amongst particles. Secondly, we show how these graphs can be induced by tree data structures which model the logical network topology of an abstract distributed computing environment. Thirdly, we present efficient distributed algorithms that achieve the desired ESS control, perform resampling and operate on forests associated with these trees

On Designing Multicore-aware Simulators for Biological Systems

The stochastic simulation of biological systems is an increasingly popular technique in bioinformatics. It often is an enlightening technique, which may however result in being computational expensive. We discuss the main opportunities to speed it up on multi-core platforms, which pose new challenges for parallelisation techniques. These opportunities are developed in two general families of solutions involving both the single simulation and a bulk of independent simulations (either replicas of derived from parameter sweep). Proposed solutions are tested on the parallelisation of the CWC simulator (Calculus of Wrapped Compartments) that is carried out according to proposed solutions by way of the FastFlow programming framework making possible fast development and efficient execution on multi-cores.Comment: 19 pages + cover pag

Performance analysis of direct N-body algorithms for astrophysical simulations on distributed systems

We discuss the performance of direct summation codes used in the simulation of astrophysical stellar systems on highly distributed architectures. These codes compute the gravitational interaction among stars in an exact way and have an O(N^2) scaling with the number of particles. They can be applied to a variety of astrophysical problems, like the evolution of star clusters, the dynamics of black holes, the formation of planetary systems, and cosmological simulations. The simulation of realistic star clusters with sufficiently high accuracy cannot be performed on a single workstation but may be possible on parallel computers or grids. We have implemented two parallel schemes for a direct N-body code and we study their performance on general purpose parallel computers and large computational grids. We present the results of timing analyzes conducted on the different architectures and compare them with the predictions from theoretical models. We conclude that the simulation of star clusters with up to a million particles will be possible on large distributed computers in the next decade. Simulating entire galaxies however will in addition require new hybrid methods to speedup the calculation.Comment: 22 pages, 8 figures, accepted for publication in Parallel Computin

Monte Carlo study of current variability in UTB SOI DG MOSFETs

The scaling of conventional silicon based MOSFETs is increasingly difficult into the nanometer regime due to short channel effects, tunneling and subthreshold leakage current. Ultra-thin body silicon-on-insulator based architectures offer a promising alternative, alleviating these problems through their geometry. However, the transport behaviour in these devices is more complex, especially for silicon thicknesses below 10 nm, with enhancement from band splitting and volume inversion competing with scattering from phonons, Coulomb interactions, interface roughness and body thickness fluctuation. Here, the effect of the last scattering mechanism on the drive current is examined as it is considered a significant limitation to device performance for body thicknesses below 5 nm. A simulation technique that properly captures non-equilibrium transport, includes quantum effects and maintains computational efficiency is essential for the study of this scattering mechanism. Therefore, a 3D Monte Carlo simulator has been developed which includes this scattering effect in an ab initio fashion, and quantum corrections using the Density Gradient formalism. Monte Carlo simulations using `frozen field' approximation have been carried out to examine the dependence of mobility on silicon thickness in large, self averaging devices. This approximation is then used to carry out statistical studies of uniquely different devices to examine the variability of on-current. Finally, Monte Carlo simulations self consistent with Poisson's equation have been carried out to further investigate this mechanism