DSPPal: AN OPEN SOURCE LIBRARY TO SUPPORT REAL-TIME IMPLEMENTATION OF DSP AND CONTROL ALGORITHMS ON A RANGE OF HARDWARE AND SOFTWARE PLATFORMS

摘要

In many third level institutions, DSP and control algorithm research and teaching is largely based on simulation tools such as Matlab, Simulink, Octave, and Scilab. While these tools clearly add to learning experience they are less effective than working with real devices which allow the student/developer to experiment with real time, resource constrained systems. Simulation can hide or over-simplify real problems such as noise, race conditions and poor performance. In addition, Matlab and Octave do not readily simulate the finite precision and word length issues that must be dealt with when algorithms are ported to digital signal processors and microcontrollers. Once the design and simulation stages are complete, algorithms are ported from the simulated environment to real hardware - a move which is problematic for many embedded systems developers. A number of solutions exist. Some developers port their application using tools provided by the DSP manufacturer that link the simulation tool to the embedded development tools. Other developers take a lower level approach and spend time learning about the target hardware. Whichever approach is taken, some knowledge of the low level hardware platform is required. This can lead to difficulties and it has been the author's experience that algorithm design and low level hardware programming represent non intersecting skill sets. This paper outlines the development and use of DSPPal - a free, open source platform A^ion layer for DSP that hides the underlying hardware/software platform details using a thin layer of software. It provides a simple and common programming interface for a diverse set of platforms ranging from PIC processors, to ARM processors to embedded Linux systems. Translation and testing of algorithms to C is assisted by the inclusion of an off-line version of the A^ion layer which is capable of sharing data with Matlab and Octave. While primarily implemented in the C programming language, ports of DSPPal to Python and Java are underway. This paper also includes some programming examples and demonstrates how an FIR filter can be designed using an offline method and moved to a real time implementation with little effort.