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Most uses of FPGAs as computational resources are relatively static, meaning that the algorithm(s) being implemented on the FPGA are created as system startup and rarely, if ever, changed during operation of the system. While there has been extensive research into dynamic reconfiguration of FPGAs (changing the hardware based algorithm on the fly to allow the FPGA to perform multiple tasks), there has not been widespread use of FPGAs for dynamically reconfigurable computing, due in large part to the system costs (measured in performance and power) of performing dynamic FPGA reprogramming. In most cases, then, the goal of FPGA based computing is to increase the raw power and computation throughput for a specific algorithm.