Parallel Discrete Event Simulation with Erlang

Discrete Event Simulation (DES) is a widely used technique in which the state of the simulator is updated by events happening at discrete points in time (hence the name). DES is used to model and analyze many kinds of systems, including computer architectures, communication networks, street traffic, and others. Parallel and Distributed Simulation (PADS) aims at improving the efficiency of DES by partitioning the simulation model across multiple processing elements, in order to enabling larger and/or more detailed studies to be carried out. The interest on PADS is increasing since the widespread availability of multicore processors and affordable high performance computing clusters. However, designing parallel simulation models requires considerable expertise, the result being that PADS techniques are not as widespread as they could be. In this paper we describe ErlangTW, a parallel simulation middleware based on the Time Warp synchronization protocol. ErlangTW is entirely written in Erlang, a concurrent, functional programming language specifically targeted at building distributed systems. We argue that writing parallel simulation models in Erlang is considerably easier than using conventional programming languages. Moreover, ErlangTW allows simulation models to be executed either on single-core, multicore and distributed computing architectures. We describe the design and prototype implementation of ErlangTW, and report some preliminary performance results on multicore and distributed architectures using the well known PHOLD benchmark.Comment: Proceedings of ACM SIGPLAN Workshop on Functional High-Performance Computing (FHPC 2012) in conjunction with ICFP 2012. ISBN: 978-1-4503-1577-

Parallelization of Plasma Physics Simulations on Massively Parallel Architectures

Proyecto de Graduación (Maestría en Ingeniería en Computación) Instituto Tecnológico de Costa Rica, Escuela de Ingeniería en Computación, 2017.Clean energy sources have increased its importance in the last few years. Because of that, the seek for more sustainable sources has been increased too. This effect made to turn the eyes of the scientific community into plasma physics, specially to the controlled fusion. This plasma physics developments have to rely on computer simulation processes before start the implementation of the respective fusion devices. The simulation process has to be done in order to detect any kind of issues on the theoretical model of the device, saving time and money. To achieve this, those computer simulation processes have to finish in a timely manner. If not, the simulation defeats its purpose. However, in recent years, computer systems have passed from an increment speed approach to a increment parallelism approach. That change represents a short stop for these applications. Because of these reasons, on this dissertation we took one plasma physics application for simulation and sped it up by implementing vectorization, shared, and distributed memory programming in a hybrid model. We ran several experiments regarding the performance improvement and the scaling of the new implementation of the application on sumpercomputers using a recent architecture, Intel Xeon Phi - Knights Landing - manycore processor. The claim of this thesis is that a plasma physics application can be parallelized achieving around 0.8 of performance under the right configuration and the right architecture

Exploring the Effects of Hyper-Threading on Parallel Simulation

none4noThis paper illustrates the effects of the Hyper- Threading processor technology on the runtime performance of a parallel and distributed simulation middleware. A preliminary analysis of the middleware design and execution parameters is given to identify the tuning parameters and to evaluate the scalability of parallel simulation. A real testbed scenario has been illustrated, based on the ARTÌS parallel and distributed simulation middleware. The experimental analysis has provided some interesting guidelines about the way to adapt the parallel and distributed simulation middleware to Hyper-Threading and to increase the execution speed of the simulation.noneBononi L.; Bracuto M.; D'Angelo G.; Donatiello L.Bononi L.; Bracuto M.; D'Angelo G.; Donatiello L