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Comparing SARS-CoV-2 Sequences using a Commercial Cloud with a Spot Instance Based Dynamic Scheduler.

, , , , , and . CCGRID, page 247-256. IEEE, (2021)

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Tuning for Tissue Image Segmentation Workflows for Accuracy and Performance., , , , , , and . CoRR, (2018)Using Multiple Fickett Bands to Accelerate Biological Sequence Comparisons., , , and . J. Comput. Biol., 26 (9): 908-922 (2019)Sensitivity analysis in digital pathology: Handling large number of parameters with compute expensive workflows., , , , , , and . Comput. Biol. Medicine, (2019)Parallel Comparison of Huge DNA Sequences in Multiple GPUs with Block Pruning., , , and . PDP, page 22-29. IEEE, (2020)Utility-Based Strategy for Balanced Cost and Availability at the Cloud Spot Market., , , and . CLOUD, page 214-218. IEEE, (2019)A Novel Statistical and Neural Network Combined Approach for the Cloud Spot Market., , , , and . IEEE Trans. Cloud Comput., 11 (1): 278-290 (January 2023)Multiagent system for dynamic resource provisioning in cloud computing platforms., , , , and . Future Gener. Comput. Syst., (2019)A Fault Tolerant and Deadline Constrained Sequence Alignment Application on Cloud-Based Spot GPU Instances., , , , , and . Euro-Par, volume 12820 of Lecture Notes in Computer Science, page 317-333. Springer, (2021)A CPU-FPGA heterogeneous approach for biological sequence comparison using high-level synthesis., , , and . Concurr. Comput. Pract. Exp., (2021)Building robust pathology image analyses with uncertainty quantification., , , , , , and . Comput. Methods Programs Biomed., (2021)