The Automated Instrumentation and Monitoring System (AIMS) reference manual

Whether a researcher is designing the 'next parallel programming paradigm,' another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of execution traces can help computer designers and software architects to uncover system behavior and to take advantage of specific application characteristics and hardware features. A software tool kit that facilitates performance evaluation of parallel applications on multiprocessors is described. The Automated Instrumentation and Monitoring System (AIMS) has four major software components: a source code instrumentor which automatically inserts active event recorders into the program's source code before compilation; a run time performance-monitoring library, which collects performance data; a trace file animation and analysis tool kit which reconstructs program execution from the trace file; and a trace post-processor which compensate for data collection overhead. Besides being used as prototype for developing new techniques for instrumenting, monitoring, and visualizing parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware test beds to evaluate their impact on user productivity. Currently, AIMS instrumentors accept FORTRAN and C parallel programs written for Intel's NX operating system on the iPSC family of multi computers. A run-time performance-monitoring library for the iPSC/860 is included in this release. We plan to release monitors for other platforms (such as PVM and TMC's CM-5) in the near future. Performance data collected can be graphically displayed on workstations (e.g. Sun Sparc and SGI) supporting X-Windows (in particular, Xl IR5, Motif 1.1.3)

Using XML and XSLT for flexible elicitation of mental-health risk knowledge

Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Methods and evolving results: Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Conclusions: Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge

NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring

Non-intrusive load monitoring, or energy disaggregation, aims to separate household energy consumption data collected from a single point of measurement into appliance-level consumption data. In recent years, the field has rapidly expanded due to increased interest as national deployments of smart meters have begun in many countries. However, empirically comparing disaggregation algorithms is currently virtually impossible. This is due to the different data sets used, the lack of reference implementations of these algorithms and the variety of accuracy metrics employed. To address this challenge, we present the Non-intrusive Load Monitoring Toolkit (NILMTK); an open source toolkit designed specifically to enable the comparison of energy disaggregation algorithms in a reproducible manner. This work is the first research to compare multiple disaggregation approaches across multiple publicly available data sets. Our toolkit includes parsers for a range of existing data sets, a collection of preprocessing algorithms, a set of statistics for describing data sets, two reference benchmark disaggregation algorithms and a suite of accuracy metrics. We demonstrate the range of reproducible analyses which are made possible by our toolkit, including the analysis of six publicly available data sets and the evaluation of both benchmark disaggregation algorithms across such data sets.Comment: To appear in the fifth International Conference on Future Energy Systems (ACM e-Energy), Cambridge, UK. 201

Eliminating Code Duplication in Cascading Style Sheets

Cascading Style Sheets (i.e., CSS) is the standard styling language, widely used for defining the presentation semantics of user interfaces for web, mobile and desktop applications. Despite its popularity, CSS has not received much attention from academia. Indeed, developing and maintaining CSS code is rather challenging, due to the inherent language design shortcomings, the interplay of CSS with other programming languages (e.g., HTML and JavaScript), the lack of empirically- evaluated coding best-practices, and immature tool support. As a result, the quality of CSS code bases is poor in many cases. In this thesis, we focus on one of the major issues found in CSS code bases, i.e., the duplicated code. In a large, representative dataset of CSS code, we found an average of 68% duplication in style declarations. To alleviate this, we devise techniques for refactoring CSS code (i.e., grouping style declarations into new style rules), or migrating CSS code to take advantage of the code abstraction features provided by CSS preprocessor languages (i.e., superset languages for CSS that augment it by adding extra features that facilitate code maintenance). Specifically for the migration transformations, we attempt to align the resulting code with manually-developed code, by relying on the knowledge gained by conducting an empirical study on the use of CSS preprocessors, which revealed the common coding practices of the developers who use CSS preprocessor languages. To guarantee the behavior preservation of the proposed transformations, we come up with a list of preconditions that should be met, and also describe a lightweight testing technique. By applying a large number of transformations on several web sites and web applications, it is shown that the transformations are indeed presentation-preserving, and can effectively reduce the amount of duplicated code in CSS