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Numerical linear algebra algorithms use the inherent elegance of matrix formulations and are usually implemented using C/C++ floating point representation. The system implementation is faced with practical constraints because these algorithms usually need to run in real time on fixed point digital signal processors (DSPs) to reduce total hardware costs. Converting the simulation model to fixed point arithmetic and  then porting it to a target DSP device is a difficult and time-consuming process. In this paper, we analyze  the conversion process. We transformed selected linear algebra algorithms from floating point to  fixed point arithmetic, and compared real-time requirements and performance between the fixed  point DSP and floating point DSP algorithm implementations. We also introduce an advanced code  optimization and an implementation by DSP-specific, fixed point C code generation. By using the  techniques described in the paper, speed can be increased by a factor of up to 10 compared to floating  point emulation on fixed point hardware

Design and Implementation of Numerical Linear Algebra Algorithms on Fixed Point DSPs