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International audience; This paper presents the Flexible Radio Kernel (FRK), a configuration and execution management environment for hybrid hardware/software flexible radio platforms. The aim of FRK is to manage platform reconfiguration for multi-mode, multi-standard operation, with different levels of abstraction.A high level framework is defined and described. Its goal is to manage multiple Medium Access Control layers and to enable cooperation algorithms for cognitive radio. A low-level environment is also available to manage platform reconfiguration for radio operations. Radios can make use of hardware or software elements, and configuration state is hidden to the high-level layers, offering pseudo concurrency (time sharing) properties independently of the nature of the elements implementation. This study presents a global view of FRK, with a specific focus on its software architecture and its support of configurable hardware. The effectiveness of the approach is demonstrated through a practical example.

International audience; Reconfigurable devices, such as FPGAs, have been known to offer an excellent performance and a high efficiency in computation. Due to their improving capacity and more efficient architecture recently, there are growing interests in using FPGAs as coprocessors in reconfigurable systems. However, FPGAs still lack the support in dynamic scheduling, e.g. to manage multiple tasks or users in a system. Performing runtime task relocation or load distribution is not possible unless the reconfigurable system supports dynamic task migration. Such ability requires the automation of configuration and context management in reconfigurable architecture, which is not available in the existing solutions.In this paper, we propose a framework for prototyping dynamic task migration between heterogeneous FPGAs. A task running on one FPGA can be suspended and resumed on another FPGA with different architecture. The extraction and restoration of FPGA registers and memory values are possible due to the task-specific extraction mechanism provided by the tasks. The proposed framework exploits a high-performance embedded processor tightly-coupled to an FPGA to automatically manage the configuration and context. It utilizes two popular heterogeneous reconfigurable systems in the implementation, Xilinx Zynq ZC706 and Altera Arria V SoC. Tests are performed using graphical and non-graphical benchmark applications and performance results are presented.