The CG domain is currently based on dataflow semantics. Dataflow models of computation in Ptolemy include synchronous dataflow (SDF), dynamic dataflow (DDF), and boolean dataflow (BDF). Both DDF and BDF are very general models of dataflow in that they are Turing equivalent. SDF is a subset of both these models. Hence, a code generation target that uses the BDF scheduler can support BDF and SDF stars but a target that uses SDF schedulers only supports SDF stars. Most targets in code generation domains use SDF schedulers and parallel schedulers which makes these targets support only SDF stars. An advantage of SDF is that compilation can be done statically; this permits very efficient code generation. While we have implemented targets that allow DDF code generation stars in the system, these targets are not in the current release. However, there are a couple of targets that use the BDF scheduler; refer to the BDF domain documentation, the section on the bdf-cg target in the CG domain documentation in the user's manual, and the section on the bdf-cgc target in the CGC domain documentation for more information on BDF semantics and the types of stars that can be supported. In this chapter, we assume that stars obey only SDF semantics since code generation for non-SDF models is still in its early stages.

The design goal of the code generation class hierarchy is to save work and to make the system more maintainable. Most of the work required to allocate memory for buffers, constants, tables, and to generate symbols that are required in code is completely processor-independent; hence these facilities are provided in the generic classes found in the $PTOLEMY/src/domains/cg/kernel directory.

A key feature of code generation domains is the notion of a target architecture. Every application must have a user-specified target architecture, selected from a set of targets supported by the user-selected domain. Every target architecture is derived from the base class Target, and controls such operations as scheduling, compiling, assembling, and downloading code. Since it controls scheduling, multiprocessor architectures can be supported with automated task partitioning and synchronization.

In the following sections, we will introduce the methods and data structures needed to write new code generation stars and targets. However, we will not document what is needed to write a new code generation domain; that discussion can be found in chapter 17. We will first introduce what is needed to write a new code generation star, introducing the concepts of code blocks, code streams and code block macros. Next we will describe the various methods which will generally use the addCode method to piece together the code blocks into the code streams. We will then go into what is required to write single-processor and multiple-processor targets. Finally we will document the various schedulers available in the code generation domains.