Systems engineers face a number of challenges when configuring and programming a complex, heterogeneous multiprocessor system of the type often used in digital signal processing applications. These include:

• How to size the system — what compute resources will it require?
• How to check if the system is configured as it should be?
• How to maximize the performance of the algorithms?
• How to move data around the system across widely differing interconnects?
• How to map the application onto the system?
• How to see how the application performs in real-time?
• How to rescale the application to a different sized system without a major rewrite?
• How to migrate the application to new processors and interconnects?

Modern toolchains are now available that are capable of helping to address these issues, allowing a significantly reduced time to solution and, thus, more rapid deployment of the application.

Sizing the System

Figure 1. Tools for checking that a valid configuration exists can save substantial time.

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One approach is to develop a tool that can model the compute performance of different processors at different clock speeds. Feeding the code snippets into this tool can allow a reasonable estimate to be made of how the algorithm will perform on a PowerPC or an FPGA, for example. In this way, the engineer can readily decide what processor types match which algorithms best, and what processor and/or FPGA resources will be needed to perform the required task in the timeframe allowed...a timeframe that is typically dictated by the incoming data rate.