TAILIEUCHUNG - High Level Synthesis: from Algorithm to Digital Circuit- P9

High Level Synthesis: from Algorithm to Digital Circuit- P9: This book presents an excellent collection of contributions addressing different aspects of high-level synthesis from both industry and academia. "High-Level Synthesis: from Algorithm to Digital Circuit" should be on each designer's and CAD developer's shelf, as well as on those of project managers who will soon embrace high level design and synthesis for all aspects of digital system design. | 66 S. Aditya and V. Kathail constraint ensures that the initiation and termination states of each task are well-defined just as they are in C. Sequential semantics By construction all process networks generated by PICO have sequential semantics as specified by the input C program . it is possible to execute one task by running the various processes to completion in the original C program order without deadlock albeit using large stream buffers. Self-cleaning It is required for the PICO input programs to execute such that no excess tokens are accumulated in any of the inter-process stream buffers between two tasks. The tool verifies this property during simulation. This property can also be stated as a constraint where the total number of tokens written to a stream during a task execution must equal the total number of tokens read out from that stream during that task. However any residual state left within the processes from executing one task can still be carried to the next task via its internal registers and shared memories. The purpose of this constraint is to ensure that FIFO queues do not grow unbounded as more and more tasks are run through the system. However it does not constrain the instantaneous access pattern of a stream during the course of a single task. That constraint is enforced by the following property. Rate-matching PICO ensures that on an average the rate of production and consumption of tokens in each stream is matched at a granularity that is much smaller that the entire task. This is achieved by adjusting the rate of computation of each process by varying the throughput of the pipelined schedule running within each process. Of course this is only a heuristic because the actual token production or consumption may be data dependent. But this analysis ensures that even during the course of a task the FIFOs can be bounded. Given the above constraints it is guaranteed that the size of the buffer needed on each stream link is bounded for a .

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