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04.07.2012 ALGLIB 3.6.0 is released.

ALGLIB 3.6.0 was released today, with new algorithms and fixes:

• Quadratic optimizer now supports arbitrary combination of boundary and linear equality/inequality constraints. New version of the optimizer uses combination of the augmented Lagrangian and active set methods.
• Spline1D unit now supports monotone cubic spline interpolation
• Support for vector-valued bilinear and bicubic splines
• Support for scalar and vector-valued trilinear (3D) splines
• Better support for sparse matrices: efficient enumeration of non-zero elements with SparseEnumerate(), faster SparseGet() for matrices stored in CRS format.
• Optmization and nonlinear fitting algorithms (LSFit, MinLM, MinBLEIC, MinLBFGS, MinCG subpackages) can verify correctness of the user-supplied gradient (the most common source of errors in numerical programs).
• Several minor fixes (see Change Log).

Commercial version of ALGLIB 3.6.0 will be delivered to customers with active support/maintenance agreement within few days. Good luck with ALGLIB!

ALGLIB 3.8.0 was released! This release features a lot of performance-related improvements, new features and bug fixes. Both editions of ALGLIB (Free and Commercial one) share following improvements:

• ranking functionality (descriptive statistics) - function which replaces data by their ranks
• new QP solver (QP-BLEIC) which is capable of solving sparse and non-convex QP problems subject to bound/linear constraints
• improved FFT (higher performance, but still single-threaded)
• better basecase C# code for matrix-matrix multiplication, which achieves performance close to that of generic C code
• a lot of minor improvements (uphill steps in BLEIC optimizer, better weight initialization for MLP's, Akima spline for less than 5 points)

ALGLIB Commercial Edition features following performance-related improvements (our former customers should upgrade their license in order to access these improvements):

• parallel ranking (descriptive statistics)
• parallel correlation/covariation functions
• parallel evaluation of distance matrix for hierarchical clustering
• parallel training of neural ensembles
• parallel cross-validation for neural networks
• parallel training of neural network
• parallel linear algebra functions (real/complex TRSM, GEMM, SYRK)

Both editions of ALGLIB share following bug fixes:

• fixed - minor bugs in implementaton of internal C++ structures (shared pool, smart pointer, proxy array/matrix)
• fixed - possible division by zero in estimator for errors-in-parameters (issue 524)
• fixed - minor error in calculation of covariance matrix for least squares fit (issue 506)
• fixed - minor bug in Student's t-test (issue 518)
• fixed - minor bug in the sign test (two sided alternative, issue 504)
• fixed - stack overflow in kd-tree construction routine (issue 521)

ALGLIB 3.8.1 is released!
This new release of ALGLIB features two major improvements in Commercial Edition:
1) C# interface to highly optimized native computational core,
2) experimental integration with Intel MKL.


1. Prior to 3.8.1, ALGLIB for C# was 100% NET application.
Being pure NET assembly, it was portable and easy to integrate into existing NET projects.
However, on some important computational problems (linear algebra, large scale data mining)
C# performance was 2x-4x times slower than that of optimized native code.

Starting from 3.8.1, ALGLIB for C# includes both pure NET computational core – and its native companion,
highly optimized native core with C# interface.
Both computational cores provide same functionality, and even more – they provide 100% identical C# interface.
You can easily plug HPC core into existing applications which use previous versions of ALGLIB.

As for ALGLIB 3.8.1, HPC core can be used only under Windows systems.
However, we plan to introduce support for LSB-compliant Linux systems in the next release.
One more limitation – HPC core is not included in ALGLIB for VB.NET,
although in next ALGLIB release VB users will have same level of performance as C# programmers.


2. Second important improvement is integration with Intel MKL, which can be accessed from C++ and C#.
Intel MKL is used internally to accelerate linear algebra algorithms.
We obtained developer's license from Intel which allows us to ship precompiled ALGLIB binaries linked with Intel MKL.

C++ version of ALGLIB now includes precompiled static library <code>alglibxx_hpc.lib</code> (ALGLIB core),
<code>mkl4alglibxx.lib</code> (MKL imports) and <code>mkl4alglibxx.dll</code> (MKL core).
When you link your application with these precompiled static/dynamic libraries,
ALGLIB will use MKL internally to provide same interface –
but with 2x-4x (depending on hardware being used) increase in linear algebra performance.
As for C#, this version of ALGLIB includes native computational core (as we told before).
It is already linked with Intel MKL, so you don't need additional steps in order to use MKL from C#.

We want to make several notes here.
First, due to licensing restrictions, you can not use Intel MKL directly.
You can use ALGLIB functionality which is internally accelerated by MKL's functions,
but you can not access these functions directly.
We do not provide you MKL header files because we do not have right to do so.
Second, because MKL support is in the experimental stage, for now we ship only Windows libraries.
Linux binaries are planned to be included in the next release of ALGLIB.

Finally, during implementation of this subproject we received several important suggestions and ideas from developers of local Intel's office,
and we would like to thank them (especially Gennady Fedorov and Sergey Maidanov) for their help.


3. These improvements can be used only by commercial users
who own license for new multi-threaded branch of ALGLIB.
If you bought your license before release of 3.8.0 and didn't upgraded your license yet,
it is good time to consider an upgrade.
Upgrade is done for free,
the only thing we need from you is a formal confirmation that you agree with new licensing terms.

In addition to improvements mentioned above, we made several minor fixes
in both Commercial and Free editions of ALGLIB
and fixed one bug in the MinBLEIC optimizer
(of course, bug fixes were included in all editions – commercial and free).