We address both challenges with Plasticine, a new spatially reconfigurable architecture designed to efficiently execute applications composed of parallel patterns.
In addition, a 5-fold reduction in the number of cycles needed to execute applications from Mibench was observed [11].
The DDDAS concept utilizes repeated simulations of an executing application to improve analytic and predictive capability by creating a synergistic feedback loop.
In particular, Dynamically Reconfigurable Embedded Systems, which exploit the advances in Field Programmable Gate Array (FPGA) technology, facilitate customisation of their hardware resources during runtime to meet the demands of executing applications.
When executing applications requiring high efficiency of image processing, press the button to enable the high-efficiency discrete display mode to provide optimal video/audio performance.
Since these concurrently executed applications might have diverse Quality of Service (QoS) requirements, it brings new challenges to network management and resource scheduling.
In particular, a debug-like mechanism offers the possibility to interpret architectural raw data observed during the simulation at application level with a function call/return granularity, thus offering the possibility to analyze the propagation of the errors in the various functionalities of the executed application.
Our solution tries to simplify things as much as possible for the user, by allowing non-specialists in programming to create a simple conceptual model of the executed application.
DDDAS entails the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the measurement process.
One essential feature of DDDAS is the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically control the measurement process.
