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Latest version 8.1.20 (August 2023)
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Extreme Optimization Numerical Libraries for .NET
What's New in Version 7.0
.NET Core and .NET Standard support
- Support for .NET Core 1.1 and 2.1.
- Support for .NET Standard 1.3 and 2.0.
- Support for .NET Framework 3.5, 4.0, 4.72 and later.
- All packages are available on the Nuget
vectors in matrix operations.
- Enable Conditional Numerical Reproducibility option for native libraries.
- Upgraded native libraries to Intel® Math Kernel Library version 2019 Update 0.
- Upgraded managed linear algebra library to LAPACK 3.7.0.
- Improved range and accuracy of matrix exponential.
- Vector Map methods that include index as delegate argument.
New matrix decompositions
- Improve performance for level 2 managed sparse BLAS.
- Improve performance for various vector operations.
- The threshold for parallel execution of vector maps can now be configured.
- The generic
class has been optimized to eliminate nearly all overhead for the most
frequently used operations on the most common argument types.
ParallelOptions is now exposed for all algorithms to enable cancellation
and other scenarios.
- Combinatorial iterators to enumerate all combinations, permutations, and Cartesian products
of sets of items.
- New overloads for numerical integration methods that take Interval objects to specify bounds.
- Inverse hyperbolic functions for decimal and quad precision numbers.
NonlinearProgram class has a new constructor that accepts variable names.
- Symbolic constraints that are linear in the variables are now recognized as such.
- The Nonlinear Program solver can now recover when it encounters an infeasible subproblem.
- Up to 30% improvement in the performance of the Linear Program solver
- Limited Memory BFGS Optimizer.
- LeastSquaresOptimizer base class for nonlinear least squares algorithms.
- Trust Region Reflexive algorithm for nonlinear least squares.
- Trust Region Reflexive algorithm option in nonlinear curve fitting.
- Improved documentation for nonlinear least squares algorithms.
Statistics and data analysis
Data access library
- Data Access Library
providing a unified API for reading and writing data frames,
matrices, and vectors.
- Reading and writing R's .rda/.rdata and .rds files.
- JSON serialization.
- Other supported formats include: delimited text (CSV, TSV...), fixed-width text,
Matrix Market, Matlab®, stata®
Want to go further back? See what was new in version 6.0.
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