Quantifying The Cost of Context Switch Chuanpeng Li, Chen Ding, and Kai Shen Department of Computer Science, University of Rochester Measuring the indirect cost of context switch is a challenging problem. In this paper, we show our result of experimentally quantifying the indirect cost of context switch using a synthetic workload. Specifically, we measure the impact of program data size and access stride on context switch cost. We also demonstrate the potential impact of OS background interrupt handling on the measurement accuracy. Such impact can be alleviated by using a multi-processor system on which one processor is employed for context switch measurement while the other runs OS background tasks.