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Quantifying Data Locality in Dynamic Parallelism in GPUs., , , , , and . SIGMETRICS (Abstracts), page 25-26. ACM, (2019)Computing with Near Data., , , , and . SIGMETRICS (Abstracts), page 27-28. ACM, (2019)Co-optimizing memory-level parallelism and cache-level parallelism., , , and . PLDI, page 935-949. ACM, (2019)CASH: compiler assisted hardware design for improving DRAM energy efficiency in CNN inference., , , , , and . MEMSYS, page 396-407. ACM, (2019)Incidental computing on IoT nonvolatile processors., , , , , , , and . MICRO, page 204-218. ACM, (2017)Spock: Exploiting Serverless Functions for SLO and Cost Aware Resource Procurement in Public Cloud., , , , , and . CLOUD, page 199-208. IEEE, (2019)Machine learning techniques for improved data prefetching., , , and . ICEAC, page 1-4. IEEE, (2015)Kube-Knots: Resource Harvesting through Dynamic Container Orchestration in GPU-based Datacenters., , , , and . CLUSTER, page 1-13. IEEE, (2019)Asymmetrically reliable caches for multicore architectures under performance and energy constraints., , , and . Cluster Computing, 19 (4): 1819-1833 (2016)Protecting Code Regions on Asymmetrically Reliable Caches., , , and . ARCS, volume 9637 of Lecture Notes in Computer Science, page 375-387. Springer, (2016)