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Dapper Description

The Distributed and Parallel Program Execution Runtime

Dapper, standing for Distributed and Parallel Program Execution Runtime, is one such tool for bridging the scientist/programmer's high level specifications that capture the essence of a program, with the low level mechanisms that reflect the unsavory realities of distributed and parallel computing. Under its dataflow-oriented approach, Dapper enables users to code locally in Java and execute globally on the cloud or grid. The user first writes codelets, or small snippets of code that perform simple tasks and do not, in themselves, constitute a complete program. Afterwards, he or she specifies how those codelets, seen as vertices in the dataflow, transmit data to each other via edge relations. The resulting directed acyclic dataflow graph is a complete program interpretable by the Dapper server, which, upon being contacted by long-lived worker clients, can coordinate a distributed execution.

To offer prospective users a glimpse of the system's capabilities, we quickly summarize many of Dapper's features that improve upon existing systems, or are new altogether:

* A code distribution system that allows the Dapper server to transmit requisite program code over the network and have clients dynamically load it. A consequence of this is that, barring external executables, updates to Dapper programs need only happen on the server-side.
* A powerful subflow embedding method for dynamically modifying the dataflow graph at runtime.
* A runtime in vanilla Java, a language that many are no doubt familiar with. Aside from the requirement of a recent JVM and optionally Graphviz Dot, Dapper is self-contained.
* A robust control protocol. The Dapper server expects any number of clients to fail, at any time, and has customizable re-execution and timeout policies to cope. Consequently, one can start and stop (long-lived) clients without fear of putting the entire system into an inconsistent state.
* Flexible semantics that allow data transfers via files or TCP streams.
* Interoperability with firewalls. Since your local cloud or grid probably sits behind a firewall, we have devised special semantics for streaming data transfers.
* Liberal licensing terms. Dapper is released under the BSD License to prevent contamination of your codebase.
* Operation as an embedded application. A user manual describes the programming API that users can follow to run the Dapper server inside an application like Apache Tomcat.
* Operation as a standalone user interface. With it, one can run off-the-shelf demos and learn core concepts from visual examples. By following a minimal set of conventions, one can then bundle one's own Dapper programs as execution archives, and then get realtime dataflow status and debugging feedback.

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