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Data storage devices are getting "smarter." Smart Flash storage devices (a.k.a. "Smart SSD") are on the horizon and will package CPU processing and DRAM storage inside a Smart SSD, and make that available to run user programs inside a Smart SSD. The focus of this paper is on exploring the opportunities and challenges associated with exploiting this functionality of Smart SSDs for relational analytic query processing. We have implemented an initial prototype of Microsoft SQL Server running on a Samsung Smart SSD. Our results demonstrate that significant performance and energy gains can be achieved by pushing selected query processing components inside the Smart SSDs. We also identify various changes that SSD device manufacturers can make to increase the benefits of using Smart SSDs for data processing applications, and also suggest possible research opportunities for the database community.

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As a variety of science applications are integrated with large-scale HPDC (High Performance Distributed Computing) technologies, timely resource allocation is revealed as a critical requirement to be considered. This paper introduces a new HPDC resource management paradigm named resource slot which defines a network of logical machines across time and space. A resource slot is not only a resource programming target but also a virtualized resource provisioning framework for a variety of resource management paradigms by encapsulating the resource management complexity. Especially, we present a resource provisioning technique named guided redundant submission (GRS), which probabilistically guarantees a timely resource slot allocation. Experimental results performed against 8 clusters in production show that about 5 redundant resources per slot can secure slot allocation with up to 36 logical machines, each cluster having an availability probability as low as 0.25 and the target success probability of slot allocation is 0.95.

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