Systems Architecture Commons^™

Grundlagenreflexionen Zur Thematik Anthropomorpher Schnittstellen, Rudolf Kaehr

Rudolf Kaehr

Report for the EMBASSI Project

Work In Progress: Automating Proportion/Period Scheduling, David Steere, Jonathan Walpole, Calton Pu

Computer Science Faculty Publications and Presentations

The recent effort to define middleware capable of supporting real-time applications creates the opportunity to raise the level of abstraction presented to the programmer. We propose that proportion/period is a better abstraction for specifying resource needs and allocation than priorities. We are currently investigating techniques to address some issues that are restricting use of proportion/period scheduling to research real-time prototypes. In particular, we are investigating techniques to automate the task of selecting proportion and period, and that allow proportion/period to incorporate job importance under overload conditions.

Two Approaches To Critical Path Scheduling For A Heterogeneous Environment, Guangxia Liu

Computer Science Theses & Dissertations

Advances in computing and networking technologies are making large scale distributed heterogeneous computing a reality. Multi-Disciplinary Optimization (MDO) is a class of applications that is being addressed under this paradigm. It consists of multiple heterogeneous modules interacting with each other to solve an overall design problem. An efficient implementation of such an application requires scheduling heterogeneous modules (with different computing and disk 1/0 requirements) on a heterogeneous set of resources (with different CPU, memory, disk IO specifications).

Given a set of tasks and a set of resources, an optimal schedule of the tasks on the resources is very hard to …

Prestructuring Neural Networks Via Extended Dependency Analysis With Application To Pattern Classification, George G. Lendaris, Thaddeus T. Shannon, Martin Zwick

Systems Science Faculty Publications and Presentations

We consider the problem of matching domain-specific statistical structure to neural-network (NN) architecture. In past work we have considered this problem in the function approximation context; here we consider the pattern classification context. General Systems Methodology tools for finding problem-domain structure suffer exponential scaling of computation with respect to the number of variables considered. Therefore we introduce the use of Extended Dependency Analysis (EDA), which scales only polynomially in the number of variables, for the desired analysis. Based on EDA, we demonstrate a number of NN pre-structuring techniques applicable for building neural classifiers. An example is provided in which EDA …

Design And Code Generation Concepts For Statechart Diagrams Of The Uml V1.1 In Concurrent Environments, Pierre Metz

Theses

This thesis deals with code generation concepts for the statechart diagrams of the UML vl.l. It explores implementation approaches for mapping statechart diagrams to code. It also focuses on modelling rules for consistent design of dynamic object behaviour. Most of the given object-oriented (00) methods have statechart diagrams as their centre. It is proposed to use statechart diagrams to model the internal behaviour of objects and lifecycles, respectively. Generally, statechart diagrams are used in the area of analysis and design of reactive systems such as realtime- and embedded-systems. This thesis introduces different existing implementation patterns and shows how they can …

Feedback Based Dynamic Proportion Allocation For Disk I/O, Dan Revel, Dylan Mcnamee, Calton Pu, David Steere, Jonathan Walpole

Computer Science Faculty Publications and Presentations

In this paper we propose to use feedback control to automatically allocate disk bandwidth in order to match the rate of disk I/O to the real-rate needs of applications. We describe a model for adaptive resource management based on measuring the relative progress of stages in a producer-consumer pipeline. We show how to use prefetching to transform a passive disk into an active data producer whose progress can be controlled via feedback. Our progress-based framework allows the integrated control of multiple resources. The resulting system automatically adapts to varying application rates as well as to varying device latencies.