Abstract. The dynamically reconfigurable hardware can be changed during run-time and more areas of an application can be mapped to the hardware in sharing fashion with potential of parallel processing. This leads to an overall improvement in performance of reconfigurable FPGA fabric as the hardware accelerator. But the concurrence in sharing FPGA architecture is becoming an important issue. In this context, we develop a simple and intuitive algorithm to explain when and why a dynamic reconfiguration solution is lead to efficient and fair allocation of FPGA resource in sharing fashion. The operation volume increase or decrease policies are examined. We formulated a set of conditions that any increase or decrease policy should satisfy to ensu...
Abstract—Dynamic parital reconfigurable FPGAs offer new design space with a variety of benefits: red...
This paper aims at defining an adaptive genetic algorithm tailored for the allocation of dynamically...
Köster M, Kalte H, Porrmann M, Rückert U. Defragmentation Algorithms for Partially Reconfigurable Ha...
Reconfigurable computing applications have traditionally had the exclusive use of the field programm...
The effective use of dynamic reconfiguration re-quires the designer to address many implementation i...
International audienceOne goal of reconfiguration is to save power and occupied resources. In this p...
Reconfigurable computing allows field programmable gate arrays (FPGA) to form a platform for develop...
Adaptive Hardware Systems can rely on software or hardware adaptation. Software adaptation can be gl...
Part 4: - SUNSET 2011 WorkshopInternational audienceDynamic reconfiguration of FPGA in the networkin...
Static FPGA (Field Programmable Gate Arrays) designs are efficient for data flow oriented applicatio...
Dynamic hardware generation reduces the number of FPGA resources needed and speeds up the applicatio...
Using dynamic partial reconfiguration (DPR), several circuits can be time-multiplexed on the same FP...
Reconfigurable systems have been shown to achieve very high computational performance. However, the ...
Abstract—Resource sharing is a classic high-level synthesis (HLS) optimization that saves area by ma...
In reconfigurable computing systems, full reconfigurable FPGA are evolving rapidly, due to their fle...
Abstract—Dynamic parital reconfigurable FPGAs offer new design space with a variety of benefits: red...
This paper aims at defining an adaptive genetic algorithm tailored for the allocation of dynamically...
Köster M, Kalte H, Porrmann M, Rückert U. Defragmentation Algorithms for Partially Reconfigurable Ha...
Reconfigurable computing applications have traditionally had the exclusive use of the field programm...
The effective use of dynamic reconfiguration re-quires the designer to address many implementation i...
International audienceOne goal of reconfiguration is to save power and occupied resources. In this p...
Reconfigurable computing allows field programmable gate arrays (FPGA) to form a platform for develop...
Adaptive Hardware Systems can rely on software or hardware adaptation. Software adaptation can be gl...
Part 4: - SUNSET 2011 WorkshopInternational audienceDynamic reconfiguration of FPGA in the networkin...
Static FPGA (Field Programmable Gate Arrays) designs are efficient for data flow oriented applicatio...
Dynamic hardware generation reduces the number of FPGA resources needed and speeds up the applicatio...
Using dynamic partial reconfiguration (DPR), several circuits can be time-multiplexed on the same FP...
Reconfigurable systems have been shown to achieve very high computational performance. However, the ...
Abstract—Resource sharing is a classic high-level synthesis (HLS) optimization that saves area by ma...
In reconfigurable computing systems, full reconfigurable FPGA are evolving rapidly, due to their fle...
Abstract—Dynamic parital reconfigurable FPGAs offer new design space with a variety of benefits: red...
This paper aims at defining an adaptive genetic algorithm tailored for the allocation of dynamically...
Köster M, Kalte H, Porrmann M, Rückert U. Defragmentation Algorithms for Partially Reconfigurable Ha...