Analysis, Tracing, Characterization and Performance Modeling of Select ASCI Applications for BlueGene/L Using Parallel Discrete Event Simulation

Caltech's Jet Propulsion Laboratory (JPL) and Center for Advanced Computer Architecture (CACR) are conducting application and simulation analyses of Blue Gene/L[1] in order to establish a range of effectiveness of the architecture in performing important classes of computations and to determine the design sensitivity of the global interconnect network in support of real world ASCI application execution

A Genetic Algorithm for UAV Routing Integrated with a Parallel Swarm Simulation

This research investigation addresses the problem of routing and simulating swarms of UAVs. Sorties are modeled as instantiations of the NP-Complete Vehicle Routing Problem, and this work uses genetic algorithms (GAs) to provide a fast and robust algorithm for a priori and dynamic routing applications. Swarms of UAVs are modeled based on extensions of Reynolds\u27 swarm research and are simulated on a Beowulf cluster as a parallel computing application using the Synchronous Environment for Emulation and Discrete Event Simulation (SPEEDES). In a test suite, standard measures such as benchmark problems, best published results, and parallel metrics are used as performance measures. The GA consistently provides efficient and effective results for a variety of VRP benchmarks. Analysis of the solution quality over time verifies that the GA exponentially improves solution quality and is robust to changing search landscapes - making it an ideal tool for employment in UAV routing applications. Parallel computing metrics calculated from the results of a PDES show that consistent speedup (almost linear in many cases) can be obtained using SPEEDES as the communication library for this UAV routing application. Results from the routing application and parallel simulation are synthesized to produce a more advanced model for routing UAVs

RITSim: distributed systemC simulation

Parallel or distributed simulation is becoming more than a novel way to speedup design evaluation; it is becoming necessary for simulating modern processors in a reasonable timeframe. As architectural features become faster, smaller, and more complex, designers are interested in obtaining detailed and accurate performance and power estimations. Uniprocessor simulators may not be able to meet such demands. The RITSim project uses SystemC to model a processor microarchitecture and memory subsystem in great detail. SystemC is a C++ library built on a discrete-event simulation kernel. Many projects have successfully implemented parallel discrete-event simulation (PDES) frameworks to distribute simulation among several hosts. The field promises significant simulation speedup, possibly leading to faster turnaround time in design space exploration and commercial production. However, parallel implementation of such simulators is not an easy task. It requires modification of the simulation kernel for effective partitioning and synchronization. This thesis explores PDES techniques and presents a distributed version of the SystemC simulation environment. With minimal user interaction, SystemC models can executed on a cluster of workstations using a message-passing library such as the Message Passing Interface (MPI). The implementation is designed for transparency; distribution and synchronization happen with little intervention by the model author. Modification of SystemC is fashioned to promote maintainability with future releases. Furthermore, only freely available libraries are used for maximum flexibility and portability

Simulation evaluation of TIMER, a time-based, terminal air traffic, flow-management concept

A description of a time-based, extended terminal area ATC concept called Traffic Intelligence for the Management of Efficient Runway scheduling (TIMER) and the results of a fast-time evaluation are presented. The TIMER concept is intended to bridge the gap between today's ATC system and a future automated time-based ATC system. The TIMER concept integrates en route metering, fuel-efficient cruise and profile descents, terminal time-based sequencing and spacing together with computer-generated controller aids, to improve delivery precision for fuller use of runway capacity. Simulation results identify and show the effects and interactions of such key variables as horizon of control location, delivery time error at both the metering fix and runway threshold, aircraft separation requirements, delay discounting, wind, aircraft heading and speed errors, and knowledge of final approach speed

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform