Programming Environments and Applications for Clusters and Grids
Supported by NSF
Period:
This project enables a "grid" to be used in the following four research projects: (1) Advanced Programming Environments for Cluster and Grids, (2) Parallel Applications for Clusters and Grids, (3) Dynamic Sequential Code Optimization, and (4) Architectures for Multimedia and Communications Applications.
The configuration permits experimentation on diverse subsystems with varying degrees of heterogeneity, up to three levels of parallelism, and a range of system sizes. The facility is used in three ways: as an experimental test-bed for systems research on clusters and grids; as a prototype for the development of parallel and distributed applications for clusters and grids; and as a cost-effective production compute server for research in architecture, compilers, and machine learning. The shared facility addresses problems critical to computational infrastructure spanning architecture, compiler, and runtime research on systems ranging from single nodes to grids, covering various application domains.
Relevant Publications:
- R. de Salvo Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons, An Inference Model for Semantic Entailment in Natural Language. Machine Learning Challenges, Evaluating Predictive Uncertainty, Visual Object Classification and Recognizing Textual Entailment, First PASCAL Machine Learning Challenges Workshop, Revised Selected Papers (2006) pp. 261--286 [bibitem]
- R. Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons, An Inference Model for Semantic Entailment in Natural Language. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2005) pp. 1678--1679 [bibitem]
- R. Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons, Knowledge Representation for Semantic Entailment and Question-Answering. IJCAI-05 Workshop on Knowledge and Reasoning for Question Answering (2005) [bibitem]
- R. de Salvo Braz, R. Girju, V. Punyakanok, D. Roth, and M. Sammons, An Inference Model for Semantic Entailment in Natural Language. Proc. of the International Joint Conference on Artificial Intelligence (IJCAI) (2005) [bibitem]
- X. Li, P. Morie, and D. Roth, Semantic Integration in Text: From Ambiguous Names to Identifiable Entities. AI Magazine. Special Issue on Semantic Integration (2005) pp. 45--68 (abstract) [bibitem]
- P. Koomen, V. Punyakanok, D. Roth, and W. Yih, Generalized Inference with Multiple Semantic Role Labeling Systems Shared Task Paper. Proc. of the Annual Conference on Computational Natural Language Learning (CoNLL) (2005) pp. 181-184 [bibitem]
- X. Li, P. Morie, and D. Roth, Identification and Tracing of Ambiguous Names: Discriminative and Generative Approaches. Proceedings of the National Conference on Artificial Intelligence (AAAI) (2004) pp. 419--424 (abstract) [bibitem]
- X. Li, P. Morie, and D. Roth, Robust Reading: Identification and Tracing of Ambiguous Names. Proc. of the Annual Meeting of the North American Association of Computational Linguistics (NAACL) (2004) pp. 17--24 (abstract) [bibitem]
- V. Punyakanok, D. Roth, W. Yih, D. Zimak, and Y. Tu, Semantic Role Labeling via Generalized Inference over Classifiers Shared Task Paper. Proc. of the Annual Conference on Computational Natural Language Learning (CoNLL) (2004) pp. 130--133 (abstract) [bibitem]
- V. Punyakanok, D. Roth, W. Yih, and D. Zimak, Natural Language Inference via Dependency Tree Mapping: An Application to Question Answering. Computational Linguistics (2004) [bibitem]
- D. Roth and W. Yih, A Linear Programming Formulation for Global Inference in Natural Language Tasks. Proceedings of AI & Math (2004) pp. 1--8 (abstract) [bibitem]
