In this paper we present a new method for high-level synthesis that enhances design flexibility, specialization and performance primarily conceived for programmable hardware. New programmable hardware devices often provide fast dedicated components that perform complex computations. Arbitrary complex computations can be efficiently extracted from the CDFG using our new graph matching constraint to produce final implementations that better suit the design to the targeted architecture. Our algorithm also reduces possible syntactic variances detecting semantically equivalent structures in the graph. This new graph matching constraint was integrated in our own Constraint Programming solver engine together with other constraints to naturally model the heterogeneous features present in the synthesis problem. The use of complex functional modules is taken into account in the optimization process during binding and scheduling yielding significantly shorter schedules and gains in terms of area and performance. We demonstrate our technique on a variety of HLS benchmarks and show that efficient design space exploration can be accomplished using this technique.

Syftet med studien är att öka kunskapen om kursplanens förankring bland programmeringslärarna. Dataunderlaget består av en enkätundersökning bland gymnasielärare iProgrammering A i Skåne. Lärarnas syn på de olika delmålen i kursplanen och sättetpå vilket dessa tillämpas i undervisningen, visas i förhållande till andra faktorer som ilitteraturen anses relevanta. Resultaten synliggör att lärarnas förhållningssätt gentemotkursplanen har mestadels gemensamma drag både när det gäller det som undervisas ochdet som utesluts. Variationerna noterades med avseende på lärarnas undervisningsbredd,elevgruppernas framtidsavsikter och språkval. Lärarna som undervisade i era kurser inomämnet tenderade att uppmärksamma er kunskapsmål. Också eleverna som senare skulleläsa Programmering B ck en mer allsidig utbildning. Däremot fanns det inte någotsom tydde på att behöriga lärare skulle skilja sig i kursplanens förverkligande. Utifrånstudieresultatet konstateras att bara hälften av kursplanens mål har ett utbrett stöd blandlärarna, vilket har konsekvenser för tillämpningen av de övergripande styrdokumenten.

Our study highlights the effects of gender-related learning styles on a computer programming course at introductory level of engineering education. It was triggered by the observation of statistically relevant under-achievements among female students over the years. We try to identify concrete differences in motivation/learning styles between genders and prove that lack of previous relevant computer experience is not the only factor to blame. The paper analyzes the situation at a LTH course from the point of view of the conflicts outlined in the literature. Data from “before-starting” questionnaires and follow ups for subsequent evaluations expose significant gender differences. Analysis of the course materials and interviews with students reveals problems of constructive alignment and discouragements to the motivation of novice programmers. We investigated several pedagogical methods to adapt teaching and evaluation in order to increase all students’ competence and at the same time reduce the gap between genders. Our key recommendation is to make the separation between the teaching of algorithms and the teaching of the specific language syntax clearer. It is our belief that good teaching of engineering subjects will enhance learning for all students

Analog circuits are often specified using non-linear equations, which are difficult to analyze. Therefore, test generation and diagnosis are problematic issues in practice. In this paper we propose a new method for diagnosis of analog circuits that uses combined information from tests at different frequencies. By solving simultaneously the resulting equations (one for each test frequency), we get a reliable method that decreases the number of possible answers to the diagnosis problem. The min-max optimization algorithm that we implemented for non-linear transfer functions gives good average runtime for diagnosis parametric faults.

It is commonly suggested that emerging technologies will revolutionize education. In this paper, two such emerging technologies, artificial intelligence (AI) and educational robots (ER), are in focus. The aim of the paper is to explore how teachers, researchers and pedagogical developers critically imagine and reflect upon how AI and robots could be used in education. The empirical data were collected from discussion groups that were part of a symposium. For both AI and ERs, the need for more knowledge about these technologies, how they could preferably be used, and how the emergence of these technologies might affect the role of the teacher and the relationship between teachers and students, were outlined. Many participants saw more potential to use AI for individualization as compared with ERs. However, there were also more concerns, such as ethical issues and economic interests, when discussing AI. While the researchers/developers to a greater extent imagined ideal future technology-rich educational practices, the practitioners were more focused on imaginaries grounded in current practice.