aformula 0.9.5
Charles Pence
June 19, 2011

Welcome to the documentation for AFormula!

AFormula is a library designed for high-performance evaluation of mathematical formulas, especially in numerical simulation and similar applications. It is heavily inspired by muParser, but is able to utilize multiple different formula-evaluation backends, including muParser itself, and the LLVM and libjit just-in-time compilers. Just-in-time compilation permits much faster formula evaluation, and the LLVM library, in particular, has been ported to many CPU architectures.

Support is included for all the standard arithmetic and comparative operators, including <=, >=, !=, ==, <, >, +, -, *, /, and ^ (exponentiation). Arbitrary variables may be defined (as pointers to double-values), and the assignment operator, =, may be used to assign values to them. A full suite of builtin functions is supported:

Finally, the constants pi and e are supported.

The order of operations is:

AFormula is designed to be quite robust to invalid formulas, and is careful to return appropriate errors when necessary.

There are two JIT backends which AFormula can use in order to compile functions on the fly: LLVM and libjit. In general, both should provide roughly the same performance, though there is a performance test included which will benchmark the library and permit selection at runtime.


AFormula provides very high performance, even in many cases surpassing what can be achieved by precompiled, native C++ code. Here are the results of a sample, representative benchmark:

Backend benchmark:

Backend 1 (muParser): 0.417541 seconds (417541 ticks)
Backend 2 (LLVM): 0.233151 seconds (233151 ticks)
Backend 3 (libjit): 0.232719 seconds (232719 ticks)
Compiled C++ (comparison): 0.235764 seconds (235764 ticks)

Note that both the JIT compilers, LLVM and libjit, perform about twice as fast as the byte-compiled muParser code, and both JIT compilers even perform 2-3% faster than the native, precompiled C++ version (g++ -O3) of the same code. Which of LLVM or libjit performs faster in a given scenario, for simple formulas, is usually a matter of chance.


The Boost C++ Libraries <> are required to build AFormula.

If you want either of the dynamic-compilation backends to be built, you will need to install either LLVM <>, or libjit <>. Note that at the time of this writing I was not able to get libjit to compile without a fair bit of hacking around on its source code.

Neither of these libraries are necessary (the included muParser backend will be built regardless), but they will provide a large speed boost.


Thanks are most obviously due to the author of muParser, Ingo Berg. Without muParser having been written, I never would have been able to start on the project that produced the need for AFormula. muParser, which is licensed under the MIT license, is Copyright (C) 2004-2006 Ingo Berg.

Also, thanks is due to the pair of massively cross-platform JIT compilation libraries, LLVM and libjit, without which a JIT-compilation backend would be impossible


The main class exported by AFormula is AFormula::Formula. See its documentation for more information.

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