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CnC is a programming model rather than a programming language. There are many implementations of the CnC model in many programming languages, including the C-based implementation built on OCR.
In CnC, programs are expressed in graph form. The CnC programmer decomposes an application into item collections, which represent data, and step collections, which represent computation. Item and step instances comprise the nodes of the CnC graph, while the edges represent data and control dependencies among the nodes.
Although these core concepts of the CnC model are common among the many implementations of the CnC model, code written for individual implementations may not be compatible. For example, Intel CnC—the flagship implementation of the CnC model—has a very different feature set from CnC-OCR. For a more detailed overview of the flavor of the CnC model used in CnC-OCR, please see this introduction to CnC (pdf).
The CnC-OCR application developer begins the development process by creating a CnC graph.
We use a textual format to represent the CnC graph, and it is saved in a file with the .cnc extension.
The graph spec file includes declarations of all item and step collections, as well as the tag functions describing the I/O for all step instances.
For more details, see the [graph specification language page](Graph Spec DSL).
Note: Although we do not provide official syntax highlighting schemes for the CnC graph syntax, we have found that highlighting the code as JavaScript tends to give pretty good results.
The CnC-OCR graph translator tool (cncocr_t) is used to parse the developer's graph specification, and use the parsed graph structure to generate a skeleton CnC-OCR project. The generated project files include:
- Makefile
- Program entry point / main function
- Graph initialization and finalization function skeletons
- Step function skeletons (suggested code) for each CnC step collection
- Additional scaffolding code to interface with OCR
The graph translator should produce a valid, but incomplete project. In other words, the generated code should compile without error, but probably won't produce any interesting results if run. The application developer needs to flesh out the provided skeleton functions with the desired computations.
The CnC-OCR application developer should only need to edit the source files in the root project directory. This includes the main function, graph initialization function, graph finalization function, and step functions. The developer might also need to add additional definitions to the provided header file. However, the developer should not need to modify any of the generated source code in the cncocr_support subdirectory, which deals directly with the underlying runtime (OCR).
The generated Makefile provides default targets for building and running the CnC-OCR application. Launching the application via make ensures that the environment is correctly configured to run OCR. Simply running make run should compile and launch the application (with no arguments). Additional parameters can be passed to the application via the WORKLOAD_ARGS variable. For example: make run WORKLOAD_ARGS="arg1 arg2 ... argN"
Please see the wiki homepage for more in-depth tutorials on using the CnC-OCR toolchain for application development.