Embedded Systems

E.1 Introduction

Two other key characteristics exist in many embedded applications: the need to minimize memory and the need to minimize power.

In practice, embedded problems are usually solved by one of three approaches:

  1. The designer uses a combined hardware/software solution that includes some custom hardware and an embedded processor core that is integrated with the custom hardware, often on the same chip.
  2. The designer uses custom software running on an off-the-shelf embedded processor.
  3. The designer uses a digital signal processor and custom software for the processor. Digital signal processors are processors specially tailored for signalprocessing applications. We discuss some of the important differences between digital signal processors and general-purpose embedded processors below.

Why do these vendors favor VLIW over superscalar? For the embedded space, code compatibility is less of a problem, and so new applications can be either hand tuned or recompiled for the newest generation of processor. The other reason superscalar excels on the desktop is because the compiler cannot predict memory latencies at compile time. In embedded, however, memory latencies are often much more predictable. In fact, hard real-time constraints force memory latencies to be statically predictable. Of course, a superscalar would also perform well in this environment with these constraints, but the extra hardware to dynamically schedule instructions is both wasteful in terms of precious chip area and in terms of power consumption. Thus VLIW is a natural choice for highperformance embedded.

Although the interprocessor interactions in such designs are highly regimented and relatively simple—consisting primarily of a simple communication channel—because much of the design is committed to silicon, ensuring that the communication protocols among the input/output processors and the general-purpose processor are correct is a major challenge in such designs.

Multiprocessing is becoming widespread in the embedded computing arena for two primary reasons. First, the issues of binary software compatibility, which plague desktop and server systems, are less relevant in the embedded space Second, the applications often have natural parallelism, especially at the high end of the embedded space

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