Predictable Real-Time Applications on Multiprocessor Systems-on-Chip

• Being predictable with respect to time is, by definition, a fundamental requirement for any real-time system. Modern multiprocessor systems impose a challenge in this context, due to resource sharing conflicts causing memory transfers to become unpredictable. In this thesis, we present a framework for achieving predictability for real-time applications running on multiprocessor system-on-chip platforms. Using a TDMA bus, worst-case execution time analysis and scheduling are done simultaneously. Since the worst-case execution times are directly dependent on the bus schedule, bus access design is of special importance. Therefore, we provide an efficient algorithm for generating bus schedules, resulting in a minimized worst-case global delay.We also present a new approach considering the average-case execution time in a predictable context. Optimization techniques for improving the average-case execution time of tasks, for which predictability with respect to time is not required, have been investigated for a long time in many different contexts. However, this has traditionally been done without paying attention to the worst-case execution time. For predictable real-time applications, on the other hand, the focus has been solely on worst-case execution time optimization, ignoring how this affects the execution time in the average case. In this thesis, we show that having a good average-case global delay can be important also for real-time applications, for which predictability is required. Furthermore, for real-time applications running on multiprocessor systems-on-chip, we present a technique for optimizing for the average case and the worst case simultaneously, allowing for a good average case execution time while still keeping the worst case as small as possible. The proposed solutions in this thesis have been validated by extensive experiments. The results demonstrate the efficiency and importance of the presented techniques.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

Nyckelord

Computer Systems

Embedded Systems

Real-Time Systems

Predictability

Multiprocessor Systems

Computer science

Datavetenskap

Publikations- och innehållstyp

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