Accurately evaluating application performance in simulated hybrid multi-tasking systems
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
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preemption in multi-tasking operating systems. Multi-tasking, and by consequence, preemption, is key to effective CPU sharing. However, it is much more expensive to save and restore context data in reconfigurable hardware than it is in traditional software. The configuration and current state comprises a large amount of data, making the transfer a long and expensive operation. In this paper, we explore alternatives to the save and restore operation for hardware multi-tasking. We compare the system performance of three alternate policies for reconfigurable hardware kernel preemption in a multi-process system: block, drop and roll. The best-performing policy is able to achieve on average within 4% of the performance of an idealized, zero-overhead save and restore method on a mixed application workload.