Intel Visual Fortran Compiler 11.0 for Windows
IMSL Fortran Library
Please note: IMSL Fortran Numerical Library is not yet available for Intel Visual Fortran Compiler version 11.0. If you purchase Intel VFC version 11.0 now, you will have the option to download and install Intel VFC version 10.1 and IMSL. Early in 2009 when IMSL is updated you can then update your current installation to Intel VFC version 11.0 and IMSL (at no cost). Alternatively, download and install Intel VFC version 11.0 now and then add IMSL once it's updated. The delay with IMSL was caused by the developers offices in Houston taking a direct hit from Hurricane Ike. Ike was one of the costliest hurricanes in U.S. history.
The IMSL Fortran Numerical Library is a comprehensive library of mathematical and statistical algorithms. It combines the powerful and flexible interface features of the Fortran language with the performance benefits of both distributed memory and shared memory multiprocessing architectures. Utilities are included to simplify large-scale computing with the ScaLAPACK library.
The strength and precision of the IMSL Numerical Libraries have been evolving steadily for over three decades. Each subroutine and algorithm has undergone rigorous testing and quality assurance, providing IMSL users with more time to focus on their application.
Powerful Interface Modules
The IMSL Fortran Numerical Library includes new powerful and flexible interface modules for all applicable routines, which accomplish the following:
- Allows users to utilise the fast, convenient optional arguments of the modern Fortran syntax for 100% of the relevant algorithms in the library, allowing for greater control and faster, simpler code development.
- Only require a short list of required arguments for each algorithm to facilitate development of simpler Fortran applications.
- Provide full depth and control via optional arguments for experienced programmers.
- Reduce development effort by checking data-type matches and array sizing at compile time.
- With operators and function modules, provide faster and more natural programming through an object-oriented approach.
- A simple and flexible interface to the library routines speeds programming and simplifies documentation.
Complete Backward Compatibility
For over two decades, the IMSL Fortran Numerical Library has maintained full backward compatibility with all previous versions of the Library. No code modifications are required for existing applications that rely on previous versions of the IMSL Fortran Numerical Library. Calls to routines from the IMSL FORTRAN 77 Library with the F77 syntax continue to function.
Fully Tested
Visual Numerics has developed over three decades of experience in testing IMSL numerical algorithms for quality and performance across an extensive range of the latest compilers and environments. Visual Numerics works with compiler partners and hardware partners to ensure a high degree of reliability and performance optimisation. This experience has allowed Visual Numerics to refine its test methods with painstaking detail. The result of this effort is a robust, sophisticated suite of test methods that allow the IMSL user to rely on the numerical analysis functionality and focus their bandwidth on their application development and testing.
SMP/OpenMP Support
The IMSL Fortran Numerical Library offers expanded SMP support for a number of parallel processing environments. Computationally intensive algorithms in the areas of linear systems and matrix manipulation, eigensystem analysis, and fast Fourier transforms (FFTs) leverage SMP capabilities on a variety of systems.
MPI Enabled
IMSL Fortran Numerical Library provides a dynamic interface for computing mathematical solutions over a distributed system via Message Passing Interface (MPI). MPI enabled routines offer a simple, reliable user interface.
The IMSL Fortran library provides a number of MPI-enabled routines with an MPI-enhanced interface that provides:
- Computational control of the server node.
- Scalability of computational resources.
- Automatic processor prioritisation.
- Self-scheduling algorithm to keep processors continuously active.
- Box data type application.
- Computational integrity.
- Dynamic error processing.
- Homogeneous and heterogeneous network functionality.
- Use of descriptive names and generic interfaces.
- A suite of testing and benchmark software.
More Robust Non-linear Optimisation
- New nonlinearly constrained optimisation routine
Time-series Algorithms
These algorithms are part of the TIMe Series Analysis and Control (TIMSAC) package developed by the Institute of Statistical Mathematics (ISM) in Japan. Time series analysis is heavily used in many fields, including economics, financial engineering, climate analysis, data mining, and many more.
- MAX_ARMA Exact maximum likelihood estimation of the parameters in a univariate Autoregressive Moving Average (ARMA) time series model.
- Useful in developing predictive models for complex time series data.
- Automatic Model Selection Fitting.
- These routines enables model fitting of time series data, such as stock prices or process data, to be fitted automatically. This automatic fitting feature thus allows model fitting to be embedded in other processes.
- Univariate and multi-variate versions available.
- Akaike's Information Criterion or Final Prediction Error methodologies available.
- Bayesian Seasonal adjustment for time series data.
- Used in areas such as economics, financial engineering, climate studies, retail sales data mining and forecasting, to name just a few.
Quasi Monte-Carlo Routine for High-dimensional Integration
- Allows numerical approximation of integrals over a very high dimensional cube.
- Can be used by financial engineers to evaluate the risk of pools of mortgages requiring integration over a 360-degree cube, for example.
New Faure Sequence Routine
- Computes a low-discrepancy sequence, which is used in Quasi Monte-Carlo analysis.
New GARCH Routine
- Used to model time series data, such as the price of oil or interest rates.