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AGORAS: A Fast Algorithm for Estimating Medoids in Large Datasets.

, , , , and . ICCS, volume 80 of Procedia Computer Science, page 1159-1169. Elsevier, (2016)

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High-Performance Techniques for Parallel I/O., , , , and . Handbook of Parallel Computing, Chapman and Hall/CRC, (2007)A novel application development environment for large-scale scientific computations., , , , , , , and . ICS, page 274-283. ACM, (2000)Data management for large-scale scientific computations in high performance distributed systems., , , , , , , , , and 1 other author(s). Clust. Comput., 3 (1): 45-60 (2000)Design, implementation and evaluation of parallel pipelined STAP on parallel computers., , , , , , and . IEEE Trans. Aerosp. Electron. Syst., 36 (2): 528-548 (2000)IOPro: a parallel I/O profiling and visualization framework for high-performance storage systems., , , , , , and . J. Supercomput., 71 (3): 840-870 (2015)A high-performance application data environment for large-scale scientific computations., , , , and . IEEE Trans. Parallel Distributed Syst., 14 (12): 1262-1274 (2003)Processor-embedded distributed smart disks for I/O-intensive workloads: architectures, performance models and evaluation., , , and . J. Parallel Distributed Comput., 64 (3): 427-446 (2004)Scalable Algorithms for MPI Intergroup Allgather and Allgatherv., , , , , and . Parallel Comput., (2019)A deep learning framework for layer-wise porosity prediction in metal powder bed fusion using thermal signatures., , , , , , , , , and 3 other author(s). J. Intell. Manuf., 34 (1): 315-329 (2023)Data Compression for the Exascale Computing Era - Survey., , , , , and . Supercomput. Front. Innov., 1 (2): 76-88 (2014)