The public defense of Hamid Reza Faragardi’s licentiate thesis in Computer Science and Engineering
Doctoral thesis and Licentiate seminars
The public defense of Hamid Reza Faragardi’s licentiate thesis in Computer Science and Engineering will take place at Mälardalen University on October 5, 2017, at 13:30 PM in room Paros, Västerås.
The title of the thesis is “Resource Optimization for Multi-processor Real-time Systems”.
The examining committee consists of Associate Professor Johan Tordsson, Umeå University, PhD Peter Wallin, Senior lecturer Cristina Seceleanu, MDH.
Among the members of the examining committee Associate Professor Johan Tordsson has been appointed the faculty examiner.
Reserve; Professor Jan Carlson, MDH.
The Licentiate thesis has serial number 263
This thesis addresses the topic of resource efficiency in multiprocessor systems in the presence of timing constraints.
Nowadays, almost wherever you look, you will find a computer system. Most of these computer systems employ a multiprocessor platform. A multiprocessor system includes a broad spectrum of computing systems ranging from a tiny chip hosting multiple cores to large geographically-distributed cloud data centers connected by the Internet. In multiprocessor systems, efficient use of computing resources is a substantial element when it comes to achieving a desirable performance for running software applications.
Most industrial applications, e.g., automotive and avionics applications, are subject to a set of real-time constraints that must be met. Such kind of applications, along with the underlying hardware and software components running the application, constitute a real-time system. In real-time systems, the first and major concern of the system designer is to provide a solution where all timing constraints are met. Therefore, in multiprocessor real-time systems, not only resource efficiency, but also meeting all the timing requirements, is a major concern.
Industrie 4.0 is the current trend in automation and manufacturing when it comes to creating next generation of smart factories. Two categories of multiprocessor systems play a significant role in the realization of such a smart factory: 1) multi-core processors which are the key computing element of embedded systems, 2) cloud computing data centers as the supplier of a massive data storage and a large computational power. Both these categories are considered in the thesis, i.e., 1) the efficient use of embedded multi-core processors where multiple processors are located on the same chip, applied to execute a real-time application, and 2) the efficient use of multi-processors within a cloud computing data center. We address these two categories of multi-processor systems separately. For each of them, we start with identifying the key challenges to achieve a resource-efficient design of the system. We also model the problem and propose smart algorithms for optimizing the efficiency of the system, while satisfying all timing constraints.