The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Static dataflow programming models are well suited to the development of embedded many-core systems. However, complex signal and media processing applications often display dynamic behavior that do not fit the classical static restrictions. We propose Transaction Parameterized Dataflow (TPDF), a new model of computation combining integer parameters—to express dynamic rates—and a new type of control...
Streaming languages are well suited to the development of embedded many-core applications that process large volumes of data with high throughput. Because they enable periodic scheduling, cyclo-static models of computation and their variants are well fitted to modern real-time applications. Nevertheless, while schedules may be functionally correct-by-construction, they can still violate timing constraints...
In this paper, we consider the problem of multiprocessor scheduling for safety-critical streaming applications modeled as acyclic data-flow graphs. To the best of our knowledge, most existing works have proposed periodic scheduling that ignore latency or can even have a negative impact on it: the results are quite far from those obtained under Self-Timed scheduling (STS). In this paper, we introduce...
Embedded many-core systems offering thousands of cores should be available in the near future. Stream programming is a particular instance of data-flow programming where computations are expressed as the data-driven execution of repetitive "filters" on data streams. Stream programming fits these manycore systems' requirements in terms of parallelism, functional determinism, and local data...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.