Single instruction multiple data code auto generation for a very long instruction words digital signal processor in sensor-based systems

The emerging applications have imposed strong requirements, such as high processing capacity, low-power consumption, reduced size and many others, on the sensor-based systems. Owing to their balanced combination of flexibility and hardware performance, digital signal processors (DSPs) have become more and more popular used in sensor-based systems. Many DSPs have adopted very long instruction words (VLIW) style architecture, for its ability to greatly enhance instruction level parallelism. However, as VLIW codes are statically scheduled, the behaviour of VLIW architecture is dominated by the efficiency of its compiler. Single instruction multiple data (SIMD) instructions, which perform multiple operations in parallel on multiple data packed in registers, have been widely used in DSPs to meet the requirements of sensor-based systems. Although hand programming still yields the best performing SIMD codes, it is both time consuming and error prone. Advanced compiler techniques to automatically generate SIMD instructions, are under urgent demand. In this study, the authors proposed an SIMD code auto generation approach for VLIW architecture. It recognises candidates of operations in the intermediate representation, evaluates the possibility of grouping them into SIMD code, reconstructs the verified ones according to the cost model and finally generates the SIMD code. The authors have implemented this approach in the compiler of a VLIW DSP named Magnolia, which is designed for sensor-based systems. The results show that the authors' approach is very efficient, and can largely enhance the performance.