High-performance programming support for multimedia document database management

In an environment in which libraries increasingly need to demonstrate their value to faculty and administrators, providing evidence of the library’s contribution to student learning through its instruction program is critical. However, building a culture of assessment can be a challenge, even if librarians recognize its importance. In order to lead change, coordinators of library instruction at institutions where librarians are also tenure-track faculty must build trust and collaboration, lead through influence, and garner support from administration for assessment initiatives. The purpose of this paper is to explore what it takes to build a culture of assessment in academic libraries where librarians are faculty through the High Performance Programming model of organizational change. The guidelines for building a culture of assessment will be exemplified by case studies at the authors’ libraries where instruction coordinators are using collaboration to build a culture of assessment with their colleagues.

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Proceedings Seventh International Workshop on Research Issues in Data Engineering. High Performance Database Management for Large-Scale Applications

10.1109/ride.1997 ◽

1997 ◽

Keyword(s):

Database Management ◽

High Performance ◽

Large Scale ◽

International Workshop ◽

Research Issues ◽

Data Engineering

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Hierarchical Architecture of Expert Systems for Database Management

Encyclopedia of Database Technologies and Applications ◽

10.4018/978-1-59140-560-3.ch046 ◽

2005 ◽

pp. 271-275 ◽

Cited By ~ 1

Author(s):

R. Manjunath

Keyword(s):

Expert System ◽

Expert Systems ◽

Database Management ◽

High Performance ◽

Hierarchical Architecture ◽

Incremental Development

Expert systems have been applied to many areas of research to handle problems effectively. Designing and implementing an expert system is a difficult job, and it usually takes experimentation and experience to achieve high performance. The important feature of an expert system is that it should be easy to modify. They evolve gradually. This evolutionary or incremental development technique has to be noticed as the dominant methodology in the expert-system area.

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Programming Paradigms in High Performance Computing

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Research and Applications in Global Supercomputing ◽

10.4018/978-1-4666-7461-5.ch013 ◽

2015 ◽

pp. 303-330

Author(s):

Venkat N Gudivada ◽

Jagadeesh Nandigam ◽

Jordan Paris

Keyword(s):

Shared Memory ◽

High Performance ◽

Programming Model ◽

Commodity Prices ◽

Massive Datasets ◽

Programming Techniques ◽

Performance Programming ◽

High Performance Computers ◽

Programming Paradigms ◽

Performance Computing

Availability of multiprocessor and multi-core chips and GPU accelerators at commodity prices is making personal supercomputers a reality. High performance programming models help apply this computational power to analyze and visualize massive datasets. Problems which required multi-million dollar supercomputers until recently can now be solved using personal supercomputers. However, specialized programming techniques are needed to harness the power of supercomputers. This chapter provides an overview of approaches to programming High Performance Computers (HPC). The programming paradigms illustrated include OpenMP, OpenACC, CUDA, OpenCL, shared-memory based concurrent programming model of Haskell, MPI, MapReduce, and message-based distributed computing model of Erlang. The goal is to provide enough detail on various paradigms to help the reader understand the fundamental differences and similarities among the paradigms. Example programs are chosen to illustrate the salient concepts that define these paradigms. The chapter concludes by providing research directions and future trends in programming high performance computers.

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