Master/worker parallel discrete event simulation

The execution of parallel discrete event simulation across metacomputing infrastructures is examined. A master/worker architecture for parallel discrete event simulation is proposed providing robust executions under a dynamic set of services with system-level support for fault tolerance, semi-automated client-directed load balancing, portability across heterogeneous machines, and the ability to run codes on idle or time-sharing clients without significant interaction by users. Research questions and challenges associated with issues and limitations with the work distribution paradigm, targeted computational domain, performance metrics, and the intended class of applications to be used in this context are analyzed and discussed. A portable web services approach to master/worker parallel discrete event simulation is proposed and evaluated with subsequent optimizations to increase the efficiency of large-scale simulation execution through distributed master service design and intrinsic overhead reduction. New techniques for addressing challenges associated with optimistic parallel discrete event simulation across metacomputing such as rollbacks and message unsending with an inherently different computation paradigm utilizing master services and time windows are proposed and examined. Results indicate that a master/worker approach utilizing loosely coupled resources is a viable means for high throughput parallel discrete event simulation by enhancing existing computational capacity or providing alternate execution capability for less time-critical codes.Ph.D.Committee Chair: Fujimoto, Richard; Committee Member: Bader, David; Committee Member: Perumalla, Kalyan; Committee Member: Riley, George; Committee Member: Vuduc, Richar

NUMA Time Warp

It is well known that Time Warp may suffer from large usage of memory, which may hamper the efficiency of the memory hierarchy. To cope with this issue, several approaches have been devised, mostly based on the reduction of the amount of used virtual memory, e.g., by the avoidance of checkpointing and the exploitation of reverse computing. In this article we present an orthogonal solution aimed at optimizing the latency for memory access operations when running Time Warp systems on Non-Uniform Memory Access (NUMA) multi-processor/multi-core computing systems. More in detail, we provide an innovative Linux-based architecture allowing per simulation-object management of memory segments made up by disjoint sets of pages, and supporting both static and dynamic binding of the memory pages reserved for an individual object to the different NUMA nodes, depending on what worker thread is in charge of running that simulation object along a given wall-clock-time window. Our proposal not only manages the virtual pages used for the live state image of the simulation object, rather, it also copes with memory pages destined to keep the simulation object's event buffers and any recoverability data. Further, the architecture allows memory access optimization for data (messages) exchanged across the different simulation objects running on the NUMA machine. Our proposal is fully transparent to the application code, thus operating in a seamless manner. Also, a free software release of our NUMA memory manager for Time Warp has been made available within the open source ROOT-Sim simulation platform. Experimental data for an assessment of our innovative proposal are also provided in this article

Automatic Algorithm Selection for Complex Simulation Problems

To select the most suitable simulation algorithm for a given task is often difficult. This is due to intricate interactions between model features, implementation details, and runtime environment, which may strongly affect the overall performance. The thesis consists of three parts. The first part surveys existing approaches to solve the algorithm selection problem and discusses techniques to analyze simulation algorithm performance.The second part introduces a software framework for automatic simulation algorithm selection, which is evaluated in the third part.Die Auswahl des passendsten Simulationsalgorithmus für eine bestimmte Aufgabe ist oftmals schwierig. Dies liegt an der komplexen Interaktion zwischen Modelleigenschaften, Implementierungsdetails und Laufzeitumgebung. Die Arbeit ist in drei Teile gegliedert. Der erste Teil befasst sich eingehend mit Vorarbeiten zur automatischen Algorithmenauswahl, sowie mit der Leistungsanalyse von Simulationsalgorithmen. Der zweite Teil der Arbeit stellt ein Rahmenwerk zur automatischen Auswahl von Simulationsalgorithmen vor, welches dann im dritten Teil evaluiert wird

Techniques for Transparent Parallelization of Discrete Event Simulation Models

Simulation is a powerful technique to represent the evolution of real-world phenomena or systems over time. It has been extensively used in different research fields (from medicine to biology, to economy, and to disaster rescue) to study the behaviour of complex systems during their evolution (symbiotic simulation) or before their actual realization (what-if analysis). A traditional way to achieve high performance simulations is the employment of Parallel Discrete Event Simulation (PDES) techniques, which are based on the partitioning of the simulation model into Logical Processes (LPs) that can execute events in parallel on different CPUs and/or different CPU cores, and rely on synchronization mechanisms to achieve causally consistent execution of simulation events. As it is well recognized, the optimistic synchronization approach, namely the Time Warp protocol, which is based on rollback for recovering possible timestamp-order violations due to the absence of block-until-safe policies for event processing, is likely to favour speedup in general application/ architectural contexts. However, the optimistic PDES paradigm implicitly relies on a programming model that shifts from traditional sequential-style programming, given that there is no notion of global address space (fully accessible while processing events at any LP). Furthermore, there is the underlying assumption that the code associated with event handlers cannot execute unrecoverable operations given their speculative processing nature. Nevertheless, even though no unrecoverable action is ever executed by event handlers, a means to actually undo the action if requested needs to be devised and implemented within the software stack. On the other hand, sequential-style programming is an easy paradigm for the development of simulation code, given that it does not require the programmer to reason about memory partitioning (and therefore message passing) and speculative (concurrent) processing of the application. In this thesis, we present methodological and technical innovations which will show how it is possible, by developing innovative runtime mechanisms, to allow a programmer to implement its simulation model in a fully sequential way, and have the underlying simulation framework to execute it in parallel according to speculative processing techniques. Some of the approaches we provide show applicability in either shared- or distributed-memory systems, while others will be specifically tailored to multi/many-core architectures. We will clearly show, during the development of these supports, what is the effect on performance of these solutions, which will nevertheless be negligible, allowing a fruitful exploitation of the available computing power. In the end, we will highlight which are the clear benefits on the programming model tha

Computer Science Research Institute 2004 annual report of activities.

This report summarizes the activities of the Computer Science Research Institute (CSRI) at Sandia National Laboratories during the period January 1, 2004 to December 31, 2004. During this period the CSRI hosted 166 visitors representing 81 universities, companies and laboratories. Of these 65 were summer students or faculty. The CSRI partially sponsored 2 workshops and also organized and was the primary host for 4 workshops. These 4 CSRI sponsored workshops had 140 participants--74 from universities, companies and laboratories, and 66 from Sandia. Finally, the CSRI sponsored 14 long-term collaborative research projects and 5 Sabbaticals

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016)

Proceedings of the First PhD Symposium on Sustainable Ultrascale Computing Systems (NESUS PhD 2016) Timisoara, Romania. February 8-11, 2016.The PhD Symposium was a very good opportunity for the young researchers to share information and knowledge, to present their current research, and to discuss topics with other students in order to look for synergies and common research topics. The idea was very successful and the assessment made by the PhD Student was very good. It also helped to achieve one of the major goals of the NESUS Action: to establish an open European research network targeting sustainable solutions for ultrascale computing aiming at cross fertilization among HPC, large scale distributed systems, and big data management, training, contributing to glue disparate researchers working across different areas and provide a meeting ground for researchers in these separate areas to exchange ideas, to identify synergies, and to pursue common activities in research topics such as sustainable software solutions (applications and system software stack), data management, energy efficiency, and resilience.European Cooperation in Science and Technology. COS

Parallel and Distributed Computing

The 14 chapters presented in this book cover a wide variety of representative works ranging from hardware design to application development. Particularly, the topics that are addressed are programmable and reconfigurable devices and systems, dependability of GPUs (General Purpose Units), network topologies, cache coherence protocols, resource allocation, scheduling algorithms, peertopeer networks, largescale network simulation, and parallel routines and algorithms. In this way, the articles included in this book constitute an excellent reference for engineers and researchers who have particular interests in each of these topics in parallel and distributed computing

Scientific Grand Challenges: Crosscutting Technologies for Computing at the Exascale - February 2-4, 2010, Washington, D.C.

The goal of the "Scientific Grand Challenges - Crosscutting Technologies for Computing at the Exascale" workshop in February 2010, jointly sponsored by the U.S. Department of Energy’s Office of Advanced Scientific Computing Research and the National Nuclear Security Administration, was to identify the elements of a research and development agenda that will address these challenges and create a comprehensive exascale computing environment. This exascale computing environment will enable the science applications identified in the eight previously held Scientific Grand Challenges Workshop Series