Tulio Tavares

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Scientific workflow systems have been introduced in response to the demand of researchers from several domains of science who need to process and analyze increasingly larger datasets. The design of these systems is largely based on the observation that data analysis applications can be composed as pipelines or networks of computations on data. In this work,(More)
Data mining techniques are becoming increasingly more popular as a reasonable means to collect summaries from the rapidly growing datasets in many areas. However, as the size of the raw data increases, parallel data mining algorithms are becoming a necessity. In this paper, we present a run-time support system that was designed to allow the efficient(More)
This paper presents a fault tolerance framework for applications that process data using a distributed network of user-defined operations in a pipelined fashion. The framework saves intermediate results and messages exchanged among application components in a distributed data management system to facilitate quick recovery from failures. The experimental(More)
Scientific Workflow Systems have been introduced in response to the demand of researchers from several domains of science who need to process and analyse increasingly larger experimental datasets. The idea is based on the observation that these operations can be composed as long pipelines of fairly standard computations that need to be executed on very(More)
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