You have the hardware and understand its architecture. You have a large problem to solve. You suspect that a parallel program may be helpful. Where do you begin? Before we can answer that question, an understanding of the software infrastructure is required. In this chapter, we will discuss general organization of parallel programs, that is, typical software architecture. Chapter 5 elaborates this further and discusses how to design solutions to different types of problems.

As we have noted, truly sequential processors hardly exist, but they execute sequential programs fully well. Some parts of the sequential program may even be executed in parallel, either directly by the hardware's design, or with the help of a parallelizing compiler. On the other hand, we are likely to achieve severely sub-par performance by relying solely on the hardware and the compiler. With only a little more thought, it is often possible to simply organize a sequential program into multiple components and turn it into a truly parallel program.

This chapter introduces parallel programming models. Parallel programming models characterize the anatomy or structure of parallel programs. This structure is somewhat more complex than that of a sequential program, and one must understand this structure to develop parallel programs. These programming models will also provide the context for the performance analysis methodology discussed in Chapter 3 as well as the parallel design techniques described in Chapter 5.

We will see in Chapter 7 that many efficient sequential algorithms are not so efficient if trivially parallelized. Many problems instead require specially designed parallel algorithms suitable for the underlying system architecture. These parallel algorithms are often designed directly in terms of these programming models.

A program broadly consists of executable parts and memory where data is held, in addition to input and output. A large parallel program usually performs input and output through a parallel file system. We will discuss parallel file systems in Section 5.4, but in the context of the current discussion they behave much like memory – data of some size can be fetched from an address or written to an address by executable parts.