Industrial Data Science
in C# and .NET:
Simple. Fast. Reliable.
 
 

ILNumerics - Technical Computing

Modern High Performance Tools for Technical

Computing and Visualization in Industry and Science

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White Paper: Numeric Computing for Industry

The ILNumerics white paper "Numeric Computing for Industry" gives a general overview of the ILNumerics Ultimate VS and its technical background. You can either browse the white paper on our website or download the PDF-file.

 

Executive Summary

Mathematical algorithms are on the rise in software development: nowadays, companies in nearly every business sector have to handle huge amounts of structured information efficiently. Recent trends such as predictive analytics have increased this demand: high performance computing is no longer just a requirement for a few high tech companies, but for all growing industries. In engineering, analytics, automotive, financial services, innovation is tightly coupled to fast mathematical algorithms.

Modern programming languages and developer tools have made it much easier to design complex software architectures. However, these tools have not yet been capable of providing the execution performance required for demanding mathematical algorithms.

That is why programming languages of the last century – such as C/C++ and FORTRAN – are still utilized for these parts of modern enterprise software. Using these technologies requires enormous effort, both in development and in maintenance.

ILNumerics cuts down the costs of development and maintenance for performance critical enterprise software by up to 50 per cent.

ILNumerics extends the modern .NET framework with efficient tools for the design and implementation of mathematical modules. It closes the gap between high performance mathematical algorithms and the efficiency provided by modern software development frameworks. ILNumerics noticeably speeds up the transition of algorithms from prototypes into productive software applications.

Complex industrial software particularly profits from ILNumerics: development cycles are much shorter; the results are more stable, and the cost of maintenance is drastically reduced.