Vectorized/batch-mode interpreter for symbolic expression trees

[bburlacu]

This ticket explores the possibility of employing batching and vectorisation techniques (ie. using dedicated datatypes from System.Numerics) to speed up the interpretation of symbolic expression trees.

Batching consists in allocating a small buffer for each instruction and performing operations on the whole buffer (instead of individual values for each row in the dataset).

Vectorisation additionally involves using SIMD (Single Instruction Multiple Data) CPU instructions to speed up batch processing.

Managed (C#) interpreter

Batch processing using the Vector<double> class in System.Numerics allows us to achieve a 2-3x speed improvement compared to the standard linear interpreter.

Native interpreter

A tree interpreter in native code (C++) can offer a significant speed advantage due to more mature backends (msvc, gcc) and features like auto-vectorization and loop unrolling.

Preliminary results show 5-10x speed improvement compared to the linear tree interpreter. We should also investigate the potential benefit of integrating fast math libraries such as ​vdt (vectorized math]) to increase computation speed.

This functionality should be implemented as an external plugin.

[bburlacu]

Preliminary results

[bburlacu]

r16266: Add native interpreter dll wrapper as external lib.

r16269: Add C++ source code

r16274: Update dll files and C++ source code to the latest version.

r16276: Add SymbolicDataAnalysisExpressionTreeNativeInterpreter which calls into the native implementation.

r16277: SymbolicDataAnalysisExpressionTreeNativeInterpreter: add EvaluatedSolutions as parameter, similar to the other interpreters.