By Deming Chen
FPGA layout Automation: A Survey is an up to date accomplished survey/tutorial of FPGA layout automation, with an emphasis at the contemporary advancements in the prior five to ten years. the focal point is at the concept and strategies which were, or probably might be, diminished to perform. It covers all significant steps in FPGA layout move: routing and site, circuit clustering, know-how mapping and architecture-specific optimization, actual synthesis, RT-level and behavior-level synthesis, and gear optimization. FPGA layout Automation: A Survey can be utilized as either a advisor for newbies who're embarking on study during this really younger but intriguing zone, and an invaluable reference for tested researchers during this box.
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Additional resources for FPGA Design Automation (Foundations and Trends in Electronic Design Automation)
Cut selection and enhancements to cut ranking will be discussed when we present details of some of the mapping algorithms. 1 Cut generation Early mapping algorithms mix cut generation and ranking to generate one or a few “good” cuts for each node. The most successful example is the FlowMap algorithm, which finds a single cut with optimal mapping depth at each node based on max-flow computation [50, 48]. It computes the optimal mapping depth of each node in the topological order from the PIs to POs based on dynamic programming.
During technology-independent optimization, we have freedom to change the network structures, but accurate estimation of the impact to downstream mapping is not available. During technology mapping, we can achieve optimal or close to optimal solutions using one of the algorithms discussed earlier. However, we are stuck with a fixed network. It is desirable to capture the interactions between logic optimization and mapping to arrive at a solution with better quality. Lossless synthesis has been proposed as way to consider technologyindependent optimization during mapping .
We may do sequential optimization such as retiming after (or before) mapping. A separate approach can miss the best overall solutions even if we can solve each individual step optimally. To obtain better overall solutions, it is desirable to combine some of the optimization steps with mapping. In this section we discuss mapping algorithms that integrate with decomposition, logic synthesis, and retiming. Mapping has also been integrated with clustering and placement; these algorithms will be presented when we discuss layout-driven synthesis.
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