Distributed Maple: parallel computer algebra in networked environments

AbstractWe describe the design and use of Distributed Maple, an environment for executing parallel computer algebra programs on multiprocessors and heterogeneous clusters. The system embeds kernels of the computer algebra system Maple as computational engines into a networked coordination layer implemented in the programming language Java. On the basis of a comparatively high-level programming model, one may write parallel Maple programs that show good speedups in medium-scaled environments. We report on the use of the system for the parallelization of various functions of the algebraic geometry library CASA and demonstrate how design decisions affect the dynamic behaviour and performance of a parallel application. Numerous experimental results allow comparison of Distributed Maple with other systems for parallel computer algebra

A parallel expert system for the control of a robotic air vehicle

Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation

VHDL-AMS based genetic optimisation of fuzzy logic controllers

Purpose – This paper presents a VHDL-AMS based genetic optimisation methodology for fuzzy logic controllers (FLCs) used in complex automotive systems and modelled in mixed physical domains. A case study applying this novel method to an active suspension system has been investigated to obtain a new type of fuzzy logic membership function with irregular shapes optimised for best performance. Design/methodology/approach – The geometrical shapes of the fuzzy logic membership functions are irregular and optimised using a genetic algorithm (GA). In this optimisation technique, VHDL-AMS is used not only for the modelling and simulation of the FLC and its underlying active suspension system but also for the implementation of a parallel GA directly in the system testbench. Findings – Simulation results show that the proposed FLC has superior performance in all test cases to that of existing FLCs that use regular-shape, triangular or trapezoidal membership functions. Research limitations – The test of the FLC has only been done in the simulation stage, no physical prototype has been made. Originality/value – This paper proposes a novel way of improving the FLC’s performance and a new application area for VHDL-AMS

Block-separable linking constraints in augmented Lagrangian coordination

Augmented Lagrangian coordination (ALC) is a provably convergent coordination method for multidisciplinary design optimization (MDO) that is able to treat both linking variables and linking functions (i.e. system-wide objectives and constraints). Contrary to quasi-separable problems with only linking variables, the presence of linking functions may hinder the parallel solution of subproblems and the use of the efficient alternating directions method of multipliers. We show that this unfortunate situation is not the case for MDO problems with block-separable linking constraints. We derive a centralized formulation of ALC for block-separable constraints, which does allow parallel solution of subproblems. Similarly, we derive a distributed coordination variant for which subproblems cannot be solved in parallel, but that still enables the use of the alternating direction method of multipliers. The approach can also be used for other existing MDO coordination strategies such that they can include block-separable linking constraints

PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications

Energy efficiency is a major concern in modern high-performance computing system design. In the past few years, there has been mounting evidence that power usage limits system scale and computing density, and thus, ultimately system performance. However, despite the impact of power and energy on the computer systems community, few studies provide insight to where and how power is consumed on high-performance systems and applications. In previous work, we designed a framework called PowerPack that was the first tool to isolate the power consumption of devices including disks, memory, NICs, and processors in a high-performance cluster and correlate these measurements to application functions. In this work, we extend our framework to support systems with multicore, multiprocessor-based nodes, and then provide in-depth analyses of the energy consumption of parallel applications on clusters of these systems. These analyses include the impacts of chip multiprocessing on power and energy efficiency, and its interaction with application executions. In addition, we use PowerPack to study the power dynamics and energy efficiencies of dynamic voltage and frequency scaling (DVFS) techniques on clusters. Our experiments reveal conclusively how intelligent DVFS scheduling can enhance system energy efficiency while maintaining performance

Änderung der Datenverteilungsfunktion im parallelen Dateisystem PVFS2

In the current PVFS2 design, load imbalances on the data servers could negatively affect the overall I/O performance. PVFS2 features a distribution interface, which can be used to implement various distribution functions. The distribution function concept is explained. A new Flexible Distribution Function is proposed, motivated by possible inhomogeneities in the hardware or access patterns. Flexibility depends on being able to redistribute data to match the access and load profile better. MPI-IO provides new data access semantics beyond the very limited capabilities of POSIX I/O. This interface is intended for use in parallel high performance applications. It is shown how it can be utilized to provide parallel redistribution for PVFS2. Additionally, some aspects of our development environment are mentioned and exemplified, including the usage of a decentralized version control system

Multidisciplinary Design Optimization with Mixed Integer Quasiseparable Subsystems

Numerous hierarchical and nonhierarchical decomposition strategies for the optimization of large scale systems, comprised of interacting subsystems, have been proposed. With a few exceptions, all of these strategies have proven theoretically unsound. Recent work considered a class of optimization problems, called quasiseparable, narrow enough for a rigorous decomposition theory, yet general enough to encompass many large scale engineering design problems. The subsystems for these problems involve local design variables and global system variables, but no variables from other subsystems. The objective function is a sum of a global system criterion and the subsystems' criteria. The essential idea is to give each subsystem a budget and global system variable values, and then ask the subsystems to independently maximize their constraint margins. Using these constraint margins, a system optimization then adjusts the values of the system variables and subsystem budgets. The subsystem margin problems are totally independent, always feasible, and could even be done asynchronously in a parallel computing context. An important detail is that the subsystem tasks, in practice, would be to construct response surface approximations to the constraint margin functions, and the system level optimization would use these margin surrogate functions. The present paper extends the quasiseparable necessary conditions for continuous variables to include discrete subsystem variables, although the continuous necessary and sufficient conditions do not extend to include integer variables