Model-based precision analysis and optimization for digital signal processors

Embedded signal processing has witnessed explosive growth in re-cent years in both scientific and consumer applications, driving the
need for complex, high-performance signal processing systems that
are largely application driven. In order to efficiently implement
these systems on programmable platforms such as digital signal
processors (DSPs), it is important to analyze and optimize the ap-
plication design from early stages of the design process. A key per-
formance concern for designers is choosing the data format. In this
work, we propose a systematic and efficient design flow involving
model-based design to analyze application data sets and precision
requirements.
We demonstrate this design flow with an exploration study into
the required precision for eigenvalue decomposition (EVD) using
the Jacobi algorithm. We demonstrate that with a high degree of
structured analysis and automation, we are able to analyze the data
set to derive an efficient data format, and optimize important parts
of the algorithm with respect to precision.