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During the past decade, divisible load theory has become a powerful tool for modeling data-intensive computational problems. DLT emerged from a desire to create intelligent sensor networks, but most recent applications involve parallel and distributed computing. Like other linear mathematical models such as Markovian queuing theory and electric resistive circuit theory, DLT offers easy computation, a schematic language, and equivalent network element modeling. While it can incorporate stochastic features, the basic model does not make statistical assumptions, which can be the Achilles' heel of a performance evaluation model.