Gheorghe Almasi

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Programming for large-scale, multicore-based architectures requires adequate tools that offer ease of programming while not hindering application performance. StarSs is a family of parallel programming models based on automatic function level parallelism that targets productivity. StarSs deploys a data-flow model: it analyses dependencies between tasks and(More)
Programming for large-scale, multicore-based architectures requires adequate tools that offer ease of programming and do not hinder application performance. StarSs is a family of parallel programming models based on automatic function-level parallelism that targets productivity. StarSs deploys a data-flow model: it analyzes dependencies between tasks and(More)
Labeling training data for machine learning algorithms is tedious, time consuming, and error prone. Consequently, it is of utmost importance to minimize the amount of labeled data that is required to learn a target concept. In the work presented here, I focus on reducing the need for labeled data in multi-view learning tasks. The key characteristic of(More)
From 02.09. to 07.09.2007, the Dagstuhl Seminar 07361 Programming Models for Ubiquitous Parallelism was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during(More)
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