IMPLEMENTATION OF A
FAST ARTIFICIAL NEURAL NETWORK LIBRARY (FANN)
October 31, 2003
Department of Computer Science
University of Copenhagen (DIKU)
The library is designed to be fast, versatile and easy to use. Several benchmarks have been executed to test the performance of the library. The results show that the fann library is significantly faster than other libraries on systems without a floating point processor, while the performance was comparable to other highly optimized libraries on systems with a floating point processor.
Keywords: ANN, artificial neural network, performance engineering, fixed point arithmetic, ANSI C.