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Using IMSL C on relational data with SourcePro DB

SourcePro DB supports a wide variety of databases and can be used to retrieve, manipulate, and analyze data, including very large data, using the statistical analysis functions provided by the IMSL C Numerical Library.

This paper provides a code example that uses SourcePro DB to harvest data from a database, analyzes that data using IMSL C, and then updates the database with the processed data.

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Tech tutorial: Embedding analytics into a database using SourcePro and IMSL C

There are numerous benefits to using embedded analytics including real-time analysis, faster results, better quality of data, and higher security.

This white paper describes how to implement embedded analytics within a database using SourcePro and the IMSL C Numerical Library, a native C library from Rogue Wave Software. It describes in detail how to implement a server-side native stored procedure leveraging IMSL C using a particular relational database management system (RDBMS). We then execute the procedure in RDBMS using SourcePro DB.

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Prototype to production with IMSL Numerical Libraries

In the development of software that requires advanced math, statistics, or analytics, there is often a disconnect early in the development process. This occurs at the transition from algorithm selection and testing to the beginning of coding in the actual compiled language. We refer to this as the prototype to production transition.

To address the disconnect during prototype to production, we are presenting a method to run IMSL Numerical Libraries routines in R or Matlab. The goal is not to replace the algorithm developer’s tool of choice but to run a compiled version of the code in parallel. Pitfalls can be caught early, and data discrepancies can be resolved quickly by running the script version and compiled version side by side.

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Leveraging high performance software in the IMSL C Numerical Library

In recent years, traditional high-performance hardware has been supplemented with graphic processing units once utilized only for 3D visualization. These general purpose graphics processing units (GPGPUs) have matured enough that function packages are now available and both single and double-precision calculations are supported. These two facts indicate the environment has reached a maturity level high enough for general purpose libraries such as IMSL to consider leveraging the hardware.

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Winbond case study

Winbond Electronics chose PV-WAVE as a development tool for their engineering data analysis database. They can now speed up the processing of large amounts of data and graphics, improve the overall efficiency, meet the requirements of the company's e-strategy, and build a web-based user interface. They have improved efficiency of yield analysis and a reduction in the number of defective products.

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Solving sparse convex quadratic programming problems with IMSL C Numerical Library

This survey article describes in some detail the mathematical and numerical aspects of function imsl_d_sparse_quadratic_prog (sparse_quadratic_prog for short), the sparse convex quadratic programming solver implemented in IMSL C Numerical Library 8.0. The solver uses an infeasible primal-dual interior-point method to find an optimal solution. All primal-dual interior-point methods are essentially variants of Newton’s method that in every iteration step solve a perturbed system of the first-order optimality conditions in order to drive the new iterate closer to the optimum. Today, such methods are widely seen as very efficient means to solve large-scale linear and convex quadratic programming problems fast and accurately.

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Standardized mixed language programming for Fortran and C

Programmers have long practiced the matter of mixed language procedure calls. This is particularly true for the programming languages C and Fortran. The use of the alternate language often results in efficient running time or the effective use of human or other resources. Prior to the Fortran 2003 standard there was silence about how the two languages inter-operated. Before this release there existed a set of differing ad hoc methods for making the inter-language calls. These typically depended on the Fortran and C compilers. The newer Fortran standard provides an intrinsic module, iso_c_binding, that permits the languages to interoperate. There remain restrictions regarding interoperable data types.

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