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Collaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU.

, , , and . SAC, page 1865-1870. ACM, (2016)

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GPU-based matrix multiplication methods for social networks analysis., , and . RACS, page 309-313. ACM, (2014)The uFLIP benchmark revisited for evaluating SSDs., , , , and . Int. J. Commun. Syst., 29 (14): 2100-2111 (2016)A Framework for Estimating Execution Times of IO Traces on SSDs., , , , and . CIKM, page 2123-2126. ACM, (2017)Collaborative processing of data-intensive algorithms with CPU, intelligent SSD, and GPU., , , and . SAC, page 1865-1870. ACM, (2016)Intelligent SSD: A turbo for big data mining., , , , , and . Comput. Sci. Inf. Syst., 13 (2): 375-394 (2016)On the Inductive Bias Transfer with Knowledge Distillation for Real-World Data., , and . AMLTS, volume 3375 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Efficient Data Augmentation Policy for Electrocardiograms., , , , and . CIKM, page 4153-4157. ACM, (2022)ECGT2T: Towards Synthesizing Twelve-Lead Electrocardiograms from Two Asynchronous Leads., , , and . ICASSP, page 1-5. IEEE, (2023)Data Locality in Graph Engines: Implications and Preliminary Experimental Results., , , , and . CIKM, page 1885-1888. ACM, (2016)On running data-intensive algorithms with intelligent SSD and host CPU: a collaborative approach., , , , and . SAC, page 2060-2065. ACM, (2015)