Currently, there are two representative non-volatile dual in-line memory module (NVDIMM) interfaces: a proprietary Intel DDR-T and the JEDEC NVDIMM-P, which are not supported by existing platforms. Adoption of new platform is costly and measuring its efficiency of migrating to the new platform is much more complex. This study is an alternative way of them—finding a new memory device that can be supported by all existing systems. In this paper, we propose an NVDIMM architecture with several system-wide mechanisms to allow the synchronous DDR4 memory interfaces to support non-deterministic (asynchronous) timing. The proposed memory architecture is implemented as a real device prototype, and also evaluated using synthetic and real workloads on an x86-64 server system.

Business planning as well as analytics on top of large-scale database systems is valuable to decision makers, but planning operations known and implemented so far are very basic. In this paper we propose a new planning operation called interval disaggregate , which goes as follows. Suppose that the planner, typically the management of a company, plans sales revenues of its products in the current year. An interval of the expected revenue for each product in the current year is computed from historical data in the database as the prediction interval of linear regression on the data. A total target revenue for the current year is given by the planner. The goal of the interval disaggregate operation is to find an appropriate disaggregation of the target revenue, considering the intervals. We formulate the problem of interval disaggregation more precisely and give solutions for the problem. Multidimensional geometry plays a crucial role in the problem formulation and the solutions. We implemented interval disaggregation into the planning engine of SAP HANA and did experiments on real-world data. Our experiments show that interval disaggregation gives more appropriate solutions with respect to historical data than the known basic disaggregation called referential disaggregation. We also show that interval disaggregation can be combined with the deseasonalization technique when the dataset shows seasonal fluctuations.

Abstract With the proliferation of various geographic databases on the Internet, we have seen increasing needs for accessing them concurrently and remotely via the Web for high‐level decision making. In this paper, we present Middleware for Efficient Access to Databases through OpenGIS Wrappers (MEADOW), an object‐oriented middleware system we have developed to meet these needs. Current OpenGIS standard addresses many interoperability issues involved in such a global utilization of geographic databases. However, existing Simple Feature specification for CORBA (SFCORBA) implementations of OpenGIS proved to be insufficient for MEADOW. The main problems are the complexity of system development and maintenance, and the inefficiency of accessing remote data servers for processing region queries. We resolved the complexity problem by automatically generating a major portion of the application code, specifically wrappers on database servers and client library modules called transparent access providers. A MEADOW view definition language was developed as a high‐level specification language for this purpose. The efficiency problem was resolved by using a region‐based group prefetching of spatial objects from a geographic region. In addition, we implemented an OID‐based semijoin for efficient global query processing, and a region‐level locking to enhance the level of concurrency among region queries. Copyright © 2002 John Wiley & Sons, Ltd

With the proliferation of various geographic database servers on the Internet, the need to access them simultaneously through the Web arises frequently for high-level decision making. The ongoing OpenGIS standard addresses many of the interoperability issues to make such global utilization of geographic databases possible. Based on the OpenGIS standard, the paper presents an object oriented architecture for the efficient Web based access to multiple geographic databases on the Internet. Called MEADOW, it provides a pair of automatically generated modules: the OpenGIS wrapper on the server side and the matching transparent access provider (TAP) on the client side. In cooperation with the wrapper, TAP supports an application's efficient access to the databases through prefetching and caching of remote objects.