In this paper, we focus on simulation techniques in order to reduce the space and time requirements for simulating large caches. First, we propose a space sampling technique to perform trace reduction for time and space. Our approach is to perform stratified sampling based on an index of locality. Our results show that the technique can provide accurate estimates of performance metrics using only a small portion of the trace references. Alternatively, we also propose a time sampling approach which performs sampling on loop iterations and requires that references between inter-loop intervals be fully simulated. We show that the time sampling technique can give representative performance results for the entire loop execution. Depending on different workloads, the approach has been shown to be very effective in reducing simulation time at the cost of small estimate errors. Lastly, we study a compensation model to estimate the miss rate of unknown references for random time sampling on short intervals.