This paper describes two software tools—a message manager and a map manager—used to implement network protocols. The tools are provided as part of the x‐kernel, an operating system kernel designed to support the construction and composition of protocols. For each tool, we briefly motivate the network task that needs to be done, give a high‐level specification of the tool, outline the algorithms and data structures used to implement the tool and give concrete examples of how the tool is used to implement real protocols. We also demonstrate how the tools, even though they are designed for general use, perform efficiently.
Real-time embedded applications such as signal-processing, surveillance and tracking, data fusion, and automated target recognition need parallel processors to meet their petformanee requirements. Unfortunately the task of developing the application .software, which must not only make efficient use of the available parallelism but must also integrate the many algorithms that comprise it, is extremely difficult. Current software design methods, including object oriented design methods, do not help in this regard as they are geared primarily for the design of sequential software.
This paper presents an overview of the Parallel Scalable Design Toolset (PSDT) being developed at Honeywell to support the design and development of real-time embedded parallel software. Software designers can use PSDT to graphically specify parallelism across collections of objects and within objects, and synchronization of data and control flows. They can also compose parallel subtasks into tasks that may in turn be a part of other tasks.PSDT can support different domain-specific parallelization paradigms. Each paradigm defines composition rules and constraints on inter-and intra-object parallelism. Since domain-specific paradigms add additional structure to the program, tools for parallelism analysis, partitioning, mapping, and code generation are able to produce near-optimum results.A prototype of the PSDT toolset is operational including a domain-specific paradigm for deterministic data-parallel periodic applications. Support for other domains and heterogeneous processing architectures is being added.
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