Theoretical Computer Science
MediaBench: a tool for evaluating and synthesizing multimedia and communicatons systems
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Computer Networks: The International Journal of Computer and Telecommunications Networking - Network processors
Probabilistic performance guarantee for real-time tasks with varying computation times
RTAS '95 Proceedings of the Real-Time Technology and Applications Symposium
Workload Characterization Model for Tasks with Variable Execution Demand
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Context-Aware Performance Analysis for Efficient Embedded System Design
Proceedings of the conference on Design, automation and test in Europe - Volume 2
A General Framework for Analysing System Properties in Platform-Based Embedded System Designs
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Abstracting functionality for modular performance analysis of hard real-time systems
Proceedings of the 2005 Asia and South Pacific Design Automation Conference
Network calculus: a theory of deterministic queuing systems for the internet
Network calculus: a theory of deterministic queuing systems for the internet
CyNC: a MATLAB/SimuLink toolbox for network calculus
Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
Modeling buffers with data refresh semantics in automotive architectures
EMSOFT '10 Proceedings of the tenth ACM international conference on Embedded software
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Modern embedded systems that are integrated as multi-processor system on chips, are often characterized by the complex behaviors and dependencies between system components. Different events that trigger such systems may cause different execution demands, depending on their event type as well as on the task they are processed by, leading to complex workload correlations. For example in data processing systems, the size of an event's payload data will typically determine its execution demand on most or all system components, leading to highly correlated workloads. Performance analysis of such systems is often difficult, and conventional analysis methods have no means to capture the possible existence of workload correlations. This leads to overly pessimistic performance analysis results, and thus to expensive system designs with considerable performance reserves. We propose an abstract model to characterize and capture workload correlations present in a system architecture, and we show how the captured additional system information can be incorporated into an existing framework for modular performance analysis of embedded systems.