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Evaluating the SAT problem on P systems for different high-performance architectures.

, , , and . The Journal of Supercomputing, 69 (1): 248-272 (2014)

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High-performance signal processing on emerging many-core architectures using cuda., and . ICME, page 1825-1828. IEEE, (2009)New data-parallel language features for sparse matrix computations., , , and . IPPS, page 742-749. IEEE Computer Society, (1995)Toward energy efficiency in heterogeneous processors: findings on virtual screening methods., , , , , and . Concurrency and Computation: Practice and Experience, 26 (10): 1832-1846 (2014)Color and texture analysis using emerging parallel architectures., , , , , and . IJHPCA, 25 (4): 404-427 (2011)Recognition of circular patterns on GPUs: Performance analysis and contributions., , and . J. Parallel Distrib. Comput., 68 (10): 1329-1338 (2008)Pathological Image Analysis Using the GPU: Stroma Classification for Neuroblastoma., , , , , and . BIBM, page 78-88. IEEE Computer Society, (2007)High Performance Computation of Moments for an Accurate Classification of Bone Tissue Images., and . HPCC, page 593-598. IEEE, (2011)CUDA Achievements and GPU Challenges Ahead.. AMDO, volume 9756 of Lecture Notes in Computer Science, page 207-217. Springer, (2016)Energy-based tuning of convolutional neural networks on multi-GPUs., , , , and . Concurrency and Computation: Practice and Experience, (2019)The GPU as an indirection engine for a fast information retrieval., and . IJEB, 3 (3/4): 316-327 (2005)