All-Pairs: An Abstraction for Data-Intensive Cloud Computing

Source: University of Notre Dame (Mendoza)

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Although modern parallel and distributed computing systems provide easy access to large amounts of computing power, it is not always easy for non-expert users to harness these large systems effectively. A large workload composed in what seems to be the obvious way by a naive user may accidentally abuse shared resources and achieve very poor performance. To address this problem, the paper proposes that production systems should provide end users with high-level abstractions that allow for the easy expression and efficient execution of data intensive workloads. The paper presents one example of an abstraction - All-Pairs - that fits the needs of several data-intensive scientific applications.
Format:PDF Size:229.60
Date:Jan 2008