We propose a performance analysis framework for adaptive real-time synchronous data flow streaming ap-plications on runtime reconfigurable FPGAs. As the main contribution, we present a constraint based ap-proach to capture both streaming application execution semantics and the varying design concerns during reconfigurations. With our event models constructed as cumulative functions on data streams, we exploit a novel compile-time analysis framework based on iterative timing phases. Finally, we implement our frame-work on a public domain constraint solver, and illustrate its capabilities in the analysis of design trade-offs due to reconfigurations with experiments
Dataflow models are often used for analysing streaming applications. The recently introduced scenari...
An embedded system is a combination of hardware and software designed to perform a dedicated functio...
Summarization: Stream join is one of the most fundamental operations to relate information from diff...
Many streaming applications composed of multiple tasks self-adapt their tasks’ execution at runtime ...
In real-time systems, the application's behavior has to be predictable at compile-time to guarantee ...
By means of partial reconfiguration, parts of the hardware can be dynamically exchanged at runtime. ...
International audienceThe aim of partially and dynamically reconfigurable hardware is to provide an ...
Embedded streaming applications require design-time temporal analysis to verify real-time constraint...
Field-Programmable Gate Arrays (FPGAs) increasingly assume roles as hardware accelerators which sign...
Of late, there has been a considerable interest in models, algorithms and method-ologies specificall...
This contribution is an extension of our work, which introduced distributed buffer schemes for runti...
This paper proposes a new design methodology to partition streaming applications onto a multi clock ...
The community of Big Data processing typically performs real-time computations on data streams with ...
Streaming applications often have latency and throughput requirements due to timing critical signal ...
Dataflow models are often used for analysing streaming applications. The recently introduced scenari...
An embedded system is a combination of hardware and software designed to perform a dedicated functio...
Summarization: Stream join is one of the most fundamental operations to relate information from diff...
Many streaming applications composed of multiple tasks self-adapt their tasks’ execution at runtime ...
In real-time systems, the application's behavior has to be predictable at compile-time to guarantee ...
By means of partial reconfiguration, parts of the hardware can be dynamically exchanged at runtime. ...
International audienceThe aim of partially and dynamically reconfigurable hardware is to provide an ...
Embedded streaming applications require design-time temporal analysis to verify real-time constraint...
Field-Programmable Gate Arrays (FPGAs) increasingly assume roles as hardware accelerators which sign...
Of late, there has been a considerable interest in models, algorithms and method-ologies specificall...
This contribution is an extension of our work, which introduced distributed buffer schemes for runti...
This paper proposes a new design methodology to partition streaming applications onto a multi clock ...
The community of Big Data processing typically performs real-time computations on data streams with ...
Streaming applications often have latency and throughput requirements due to timing critical signal ...
Dataflow models are often used for analysing streaming applications. The recently introduced scenari...
An embedded system is a combination of hardware and software designed to perform a dedicated functio...
Summarization: Stream join is one of the most fundamental operations to relate information from diff...