Efficiency of linked cell algorithms

The linked cell list algorithm is an essential part of molecular simulation software, both molecular dynamics and Monte Carlo. Though it scales linearly with the number of particles, there has been a constant interest in increasing its efficiency, because a large part of CPU time is spent to identify the interacting particles. Several recent publications proposed improvements to the algorithm and investigated their efficiency by applying them to particular setups. In this publication we develop a general method to evaluate the efficiency of these algorithms, which is mostly independent of the parameters of the simulation, and test it for a number of linked cell list algorithms. We also propose a combination of linked cell reordering and interaction sorting that shows a good efficiency for a broad range of simulation setups.Comment: Submitted to Computer Physics Communications on 22 December 2009, still awaiting a referee repor

Measurement of low-energy antiproton detection efficiency in BESS below 1 GeV

An accelerator experiment was performed using a low-energy antiproton beam to measure antiproton detection efficiency of BESS, a balloon-borne spectrometer with a superconducting solenoid. Measured efficiencies showed good agreement with calculated ones derived from the BESS Monte Carlo simulation based on GEANT/GHEISHA. With detailed verification of the BESS simulation, the relative systematic error of detection efficiency derived from the BESS simulation has been determined to be $\pm$5%, compared with the previous estimation of $\pm$15% which was the dominant uncertainty for measurements of cosmic-ray antiproton flux.Comment: 13 pages, 7 figure

Enhancing simulation of efficiency with analytical tools

Some means of combining both computer simulation and anlytical techniques are indicated in order to mutually enhance their efficiency as design tools and to motivate those involved in engineering design to consider using such combinations. While the idea is not new, heavy reliance on computers often seems to overshadow the potential utility of analytical tools. Although the example used is drawn from the area of dynamics and control, the principles espoused are applicable to other fields. In the example the parameter plane stability analysis technique is described briefly and extended beyond that reported in the literature to increase its utility (through a simple set of recursive formulas) and its applicability (through the portrayal of the effect of varying the sampling period of the computer). The numerical values that were rapidly selected by analysis were found to be correct for the hybrid computer simulation for which they were needed. This obviated the need for cut-and-try methods to choose the numerical values, thereby saving both time and computer utilization

An intelligent processing environment for real-time simulation

The development of a highly efficient and thus truly intelligent processing environment for real-time general purpose simulation of continuous systems is described. Such an environment can be created by mapping the simulation process directly onto the University of Alamba's OPERA architecture. To facilitate this effort, the field of continuous simulation is explored, highlighting areas in which efficiency can be improved. Areas in which parallel processing can be applied are also identified, and several general OPERA type hardware configurations that support improved simulation are investigated. Three direct execution parallel processing environments are introduced, each of which greatly improves efficiency by exploiting distinct areas of the simulation process. These suggested environments are candidate architectures around which a highly intelligent real-time simulation configuration can be developed