Group Communication Patterns for High Performance Computing in Scala

We developed a Functional object-oriented Parallel framework (FooPar) for high-level high-performance computing in Scala. Central to this framework are Distributed Memory Parallel Data structures (DPDs), i.e., collections of data distributed in a shared nothing system together with parallel operations on these data. In this paper, we first present FooPar's architecture and the idea of DPDs and group communications. Then, we show how DPDs can be implemented elegantly and efficiently in Scala based on the Traversable/Builder pattern, unifying Functional and Object-Oriented Programming. We prove the correctness and safety of one communication algorithm and show how specification testing (via ScalaCheck) can be used to bridge the gap between proof and implementation. Furthermore, we show that the group communication operations of FooPar outperform those of the MPJ Express open source MPI-bindings for Java, both asymptotically and empirically. FooPar has already been shown to be capable of achieving close-to-optimal performance for dense matrix-matrix multiplication via JNI. In this article, we present results on a parallel implementation of the Floyd-Warshall algorithm in FooPar, achieving more than 94 % efficiency compared to the serial version on a cluster using 100 cores for matrices of dimension 38000 x 38000

Research on an expert system for database operation of simulation-emulation math models. Volume 1, Phase 1: Results

The results of the first phase of Research on an Expert System for Database Operation of Simulation/Emulation Math Models, is described. Techniques from artificial intelligence (AI) were to bear on task domains of interest to NASA Marshall Space Flight Center. One such domain is simulation of spacecraft attitude control systems. Two related software systems were developed to and delivered to NASA. One was a generic simulation model for spacecraft attitude control, written in FORTRAN. The second was an expert system which understands the usage of a class of spacecraft attitude control simulation software and can assist the user in running the software. This NASA Expert Simulation System (NESS), written in LISP, contains general knowledge about digital simulation, specific knowledge about the simulation software, and self knowledge

Developing a labelled object-relational constraint database architecture for the projection operator

Current relational databases have been developed in order to improve the handling of stored data, however, there are some types of information that have to be analysed for which no suitable tools are available. These new types of data can be represented and treated as constraints, allowing a set of data to be represented through equations, inequations and Boolean combinations of both. To this end, constraint databases were defined and some prototypes were developed. Since there are aspects that can be improved, we propose a new architecture called labelled object-relational constraint database (LORCDB). This provides more expressiveness, since the database is adapted in order to support more types of data, instead of the data having to be adapted to the database. In this paper, the projection operator of SQL is extended so that it works with linear and polynomial constraints and variables of constraints. In order to optimize query evaluation efficiency, some strategies and algorithms have been used to obtain an efficient query plan. Most work on constraint databases uses spatiotemporal data as case studies. However, this paper proposes model-based diagnosis since it is a highly potential research area, and model-based diagnosis permits more complicated queries than spatiotemporal examples. Our architecture permits the queries over constraints to be defined over different sets of variables by using symbolic substitution and elimination of variables.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-0

Connectionist Inference Models

The performance of symbolic inference tasks has long been a challenge to connectionists. In this paper, we present an extended survey of this area. Existing connectionist inference systems are reviewed, with particular reference to how they perform variable binding and rule-based reasoning, and whether they involve distributed or localist representations. The benefits and disadvantages of different representations and systems are outlined, and conclusions drawn regarding the capabilities of connectionist inference systems when compared with symbolic inference systems or when used for cognitive modeling

X-TREAM project: Task 1b - Survey of the state-of-the-art numerical techniques for solving coupled non-linear multi-physics equations

Nowadays, the precise modeling of a nuclear reactor core is a challenge. This task involves several aspects, from the computational power needed to perform simulations, to the physics and analysis of the outcome. The need to better understand the physical phenomena is critical in order to quantify and qualify nuclear safety parameters. Currently, substantial research has been done in order to optimize the prediction capabilities of coupled codes. The need to better understand the multi-physics coupling between the neutronics and the thermal-hydraulics is required. In this report, state-of-the art of current methods and numerical techniques used in coupled codes are highlighted. A better understanding of the numerical schemes will allows selecting an appropriate algorithm to be implemented in POLCA-T. POLCA-T is the coupled code developed by Westinghouse that currently uses an explicit approach to couple the neutronics (POLCA7) and thermal-hydraulics (RIGEL). The final objective is to implement the concept of the Jacobian-free Newton-Krylov method, which will be used for solving the nonlinear equations which rise from the coupled solution

A Maple Toolchain for Rigid Body Dynamics of Serial, Hybrid and Parallel Robots

A new Maple toolchain for generating rigid body dynamics in symbolic form for robot manipulators is presented. The peculiarity compared to existing tools lies in the framework of Bash scripts controlling the full workflow of the toolchain with a high degree of automation. The optimized Matlab code generated by Maple is automatically converted to function files with proper documentation and input assertions. This renders manual post-processing of the results unnecessarily. The focus of the paper is on the implemented unit-testing framework according to the method of test-driven development. By providing the test framework together with the generated code in a stand-alone version, a good test coverage and a good software quality can be achieved. The results of the open source project provide a basis for dynamics simulations for robot dimensional synthesis or in model-based control of robot manipulators in research or in industrial context. The general software approach can be applied to other fields where theoretical models are derived with Maple