GreenBus: a generic interconnect fabric for transaction level modelling
Proceedings of the 43rd annual Design Automation Conference
Fast and accurate transaction level models using result oriented modeling
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Towards a Unified Execution Model for Transactions in TLM
MEMOCODE '07 Proceedings of the 5th IEEE/ACM International Conference on Formal Methods and Models for Codesign
Multi-Accuracy Power and Performance Transaction-Level Modeling
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Fault tolerant network on chip switching with graceful performance degradation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems - Special issue on the 2009 ACM/IEEE international symposium on networks-on-chip
Modeling constructs and kernel for parallel simulation of accuracy adaptive TLMs
Proceedings of the Conference on Design, Automation and Test in Europe
White box performance analysis considering static non-preemptive software scheduling
Proceedings of the Conference on Design, Automation and Test in Europe
Automatic generation of high-speed accurate TLM models for out-of-order pipelined bus
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on ESTIMedia'10
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Simulation of transaction level models (TLMs) is an established embedded systems design technique. Its use cases include virtual prototyping for early software development, platform simulation for design space exploration, and reference modelling for verification. The different use cases mandate different trade-offs between simulation performance and accuracy. Therefore, multiple TLM abstraction layers have been defined of which one has to be chosen and integrated into the system model prior to simulation. In this contribution we present a modelling technique that allows covering several layers in a single model and switching between the layers at any time, in particular dynamically during simulation. This feature is employed to automatically adapt simulation accuracy to an appropriate level depending on the model's state, leading to an improved trade-off between simulation performance and accuracy.