Cluster Computing in the Classroom: Topics, Guidelines, and Experiences

With the progress of research on cluster computing, more and more universities have begun to offer various courses covering cluster computing. A wide variety of content can be taught in these courses. Because of this, a difficulty that arises is the selection of appropriate course material. The selection is complicated by the fact that some content in cluster computing is also covered by other courses such as operating systems, networking, or computer architecture. In addition, the background of students enrolled in cluster computing courses varies. These aspects of cluster computing make the development of good course material difficult. Combining our experiences in teaching cluster computing in several universities in the USA and Australia and conducting tutorials at many international conferences all over the world, we present prospective topics in cluster computing along with a wide variety of information sources (books, software, and materials on the web) from which instructors can choose. The course material described includes system architecture, parallel programming, algorithms, and applications. Instructors are advised to choose selected units in each of the topical areas and develop their own syllabus to meet course objectives. For example, a full course can be taught on system architecture for core computer science students. Or, a course on parallel programming could contain a brief coverage of system architecture and then devote the majority of time to programming methods. Other combinations are also possible. We share our experiences in teaching cluster computing and the topics we have chosen depending on course objectives

Finding the Balance Between Guidance and Independence in Cybersecurity Exercises

Abstract In order to accomplish cyber security tasks, one needs to know how to analyze complex data and when and how to use tools. Many hands-on exercises for cybersecurity courses have been developed to teach these skills. There is a spectrum of ways that these exercises can be taught. On one end of the spectrum are prescriptive exercises, in which students follow step-by-step instructions to run scripted exploits, perform penetration testing, do security audits, etc. On the other end of the spectrum are open-ended exercises and capture-the-flag activities, where little guidance is given on how to proceed. This paper reports on our experience with trying to find a balance between these extremes in the context of one of the suite of cybersecurity exercises that we have developed in the EDURange framework 1 . The particular exercise that we present teaches students about dynamic analysis of binaries using strace. We have found that students are most successful in these exercises when they are given the right amount of prerequisite knowledge and guidance as well as some opportunity to find creative solutions. Our scenarios are specifically designed to develop analysis skills and the security mindset in students and to complement the theoretical aspects of the discipline and develop practical skills

Latency Avoiding by Adequate Mapping

What to do if the number of processes your algorithm uses in parallel is bigger than the number of processors your parallel machine has? That's when mapping comes into play. But let's be careful: Mapping affects the load balance and the number of remote accesses (with the latter causing latency). This paper discusses adequate mapping for two well-known algorithms (summing an array, matrix-vector multiplication) and shows the resulting effects (using pC++ and the TAU environment). CONTENTS 2 Contents 1 Introduction 3 1.1 An example of mapping : : : : : : : : : : : : : : : : : : : : : : : 3 1.2 Arising questions : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 1.3 The scope of mapping : : : : : : : : : : : : : : : : : : : : : : : : 3 1.4 Latency avoiding : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 1.5 Current research in mapping : : : : : : : : : : : : : : : : : : : : 4 2 Adequate mapping 5 2.1 What choices do we have? : : : : : : : : : : : : : : : : : : : : : : ..

Abstract MIT Technology Review lists sensor networks as one of “Ten Emerging Technologies That Will

Change the World ” [1]. This paper extends our earlier paper [7], and describes three additional lab exercises, derived from the TinyOS tutorials and using MicaZ motes, that are suitable for activity-driven teaching of sensor networks to undergraduate students. One exercise includes some actual coding, and in another exercise, a mote also logs data to local storage, and reports it back to the PC at a later time. We describe our experiences, lessons and code alterations. Keywords: Wireless sensor networks, Education, TinyOS, MicaZ motes, Pervasive computing