Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Por analysis early in the design cycle is critical for the design of low por systems. With the move to system-level specifications and design methodologies, there has been significant research interest in system-level por estimation. Hover, as demonstrated in this paper, the addition of por estimation capabilities to system-level simulation tools can significantly degrade simulation efficiency (up to 8.5/spl times/), limiting the use of por estimation during long simulation rum, and the ability to perform extensive design space exploration. Some por modeling techniques for system components provide "local" tradeoffs beten por estimation accuracy and computational cost This work addresses a complementary problem - the optimized integration and usage of heterogeneous component por models within a system-level simulation framework.  view system-level por estimation as a global deployment of computational effort (the effort required to perform por estimation) over space (the different components) and time (the duration of the simulation).  illustrate the advantages of optimizing the allocation of por estimation effort based on run-time variations of component-level, as ll as system-level por consumption characteristics. To achieve this,  have developed a novel por estimation framework, based on a network of por monitors. Por monitors observe component- and system-level execution and por statistics at run time, based on which they (I) select beten multiple alternative por models for each component, and/or (II) configure the component por models, to best negotiate the trade-off beten efficiency and accuracy. In effect, the por monitor network performs a coordinated, adaptive, spatio-temporal allocation of computational effort for por estimation. Experiments conducted on a commercial system-level simulation framework and system-on-chip platform demonstrate that the proposed techniques yield large reductions in por estimation overhead (nearly an order of magnitude), while minimally impacting por estimation accuracy.
['Nikhil Bansal', 'Kanishka Lahiri', 'Anand Raghunathan', 'Srimat T. Chakradhar']
I am writing a research paper on a idea Power monitors: a framework for system-level power estimation using heterogeneous power models
[{"from": "human", "value": "I am writing a research paper on a idea Power monitors: a framework for system-level power estimation using heterogeneous power models"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Por analysis early in the design cycle is critical for the design of low por systems. With the move to system-level specifications and design methodologies, there has been significant research interest in system-level por estimation. Hover, as demonstrated in this paper, the addition of por estimation capabilities to system-level simulation tools can significantly degrade simulation efficiency (up to 8.5/spl times/), limiting the use of por estimation during long simulation rum, and the ability to perform extensive design space exploration. Some por modeling techniques for system components provide \"local\" tradeoffs beten por estimation accuracy and computational cost This work addresses a complementary problem - the optimized integration and usage of heterogeneous component por models within a system-level simulation framework.  view system-level por estimation as a global deployment of computational effort (the effort required to perform por estimation) over space (the different components) and time (the duration of the simulation).  illustrate the advantages of optimizing the allocation of por estimation effort based on run-time variations of component-level, as ll as system-level por consumption characteristics. To achieve this,  have developed a novel por estimation framework, based on a network of por monitors. Por monitors observe component- and system-level execution and por statistics at run time, based on which they (I) select beten multiple alternative por models for each component, and/or (II) configure the component por models, to best negotiate the trade-off beten efficiency and accuracy. In effect, the por monitor network performs a coordinated, adaptive, spatio-temporal allocation of computational effort for por estimation. Experiments conducted on a commercial system-level simulation framework and system-on-chip platform demonstrate that the proposed techniques yield large reductions in por estimation overhead (nearly an order of magnitude), while minimally impacting por estimation accuracy."}]