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The application of hardware-parameterized models to distributed systems can result in omission of key bottlenecks such as the full cost of inter-node communication in a shared memory cluster. However, inclusion in the model of message characteristics and complex memory hierarchies may result in impractical models. Nonetheless, the growing gap between memory and CPU performance combined with the trend toward large scale clustered shared memory platforms implies an increased need to consider the impact of local memory communication on parallel processing in distributed systems. We present a simple and useful model of point-to-point memory communication to predict and analyze the latency of memory copy, pack and unpack. We use the model to isolate contributions of hardware, middleware, and software to data transfers on Intel- and MIPS-based platforms.