Modern multimedia systems are becoming increasingly multiprocessor and heterogeneous to match the high performance and low power demands placed on them by the large number of applications. The concurrent execution of these applications causes interference and unpredictability in the performance of these systems. In Multimedia Multiprocessor Systems, an analysis mechanism is presented to accurately predict the performance of multiple applications executing concurrently. With high consumer demand the time-to-market has become significantly lower. To cope with the complexity in designing such systems, an automated design-flow is needed that can generate systems from a high-level architectural description such that they are not error-prone and consume less time. Such a design methodology is presented for multiple use-cases -- combinations of active applications. A resource manager is also presented to manage the various resources in the system, and to achieve the goals of performance prediction, admission control and budget enforcement.

Preface. 1. TRENDS AND CHALLENGES IN MULTIMEDIA SYSTEMS. 1 Trends in Multimedia Systems Applications. 2 Trends in Multimedia Systems Design. 3 Key Challenges in Multimedia Systems Design. 4 Design Flow. 5 Book Overview. 2. APPLICATION MODELING AND SCHEDULING. 1 Application Model and Specification. 2 Introduction to SDF Graphs. 3 Comparison of Dataflow Models. 4 Performance Modeling. 5 Scheduling Techniques for Dataflow Graphs. 6 Analyzing Application Performance on Hardware. 7 Composability. 8 Static vs Dynamic Ordering. 9 Conclusions. 3. PROBABILISTIC PERFORMANCE PREDICTION. 1 Basic Probabilistic Analysis. 2 Iterative Analysis. 3 Experiments. 4 Suggested Readings. 5 Conclusions. 4. RESOURCE MANAGEMENT. 1 Off-line Derivation of Properties. 2 On-line Resource Manager. 3 Achieving Predictability through Suspension. 4 Experiments. 5 Suggested Readings. 6 Conclusions. 5. MULTIPROCESSOR SYSTEM DESIGN AND SYNTHESIS. 1 Performance Evaluation Framework. 2 MAMPS Flow Overview. 3 Tool Implementation. 4 Experiments and Results. 5 Suggested Readings. 6 Conclusions. 6. MULTIPLE USE-CASES SYSTEM DESIGN. 1 Merging Multiple Use-cases. 2 Use-case Partitioning. 3 Estimating Area: Does it Fit? 4 Experiments and Results. 5 Suggested Readings. 6 Conclusions. 7. CONCLUSIONS AND OPEN PROBLEMS. 1 Conclusions. 2 Open Problems. References. Index.