Performance modeling of virtualized custom logic computations

Virtualization of custom logic computations (i.e., by sharing a fixed function across distinct data streams), provides a means of reusing limited hardware resources. This is common practice in traditional processors where more than one user can share processor resources. In this paper, we virtualize a custom logic block using C-slow techniques to support fine-grain context-switching. We then develop and present an analytic model for several performance measures (throughput, latency, input queue occupancy) for both fine- and coarse-grained context switching. Next, we calibrate the analytic performance model with empirical measurements. We then validate the model via discrete-event simulation and use the model to predict the performance and develop optimal schedules for virtualized logic computations.