Developing Synthesis Flows Without Human Knowledge
April 16, 2018 Β· Declared Dead Β· π Design Automation Conference
"No code URL or promise found in abstract"
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Authors
Cunxi Yu, Houping Xiao, Giovanni De Micheli
arXiv ID
1804.05714
Category
cs.DC: Distributed Computing
Cross-listed
cs.LG
Citations
99
Venue
Design Automation Conference
Last Checked
4 months ago
Abstract
Design flows are the explicit combinations of design transformations, primarily involved in synthesis, placement and routing processes, to accomplish the design of Integrated Circuits (ICs) and System-on-Chip (SoC). Mostly, the flows are developed based on the knowledge of the experts. However, due to the large search space of design flows and the increasing design complexity, developing Intellectual Property (IP)-specific synthesis flows providing high Quality of Result (QoR) is extremely challenging. This work presents a fully autonomous framework that artificially produces design-specific synthesis flows without human guidance and baseline flows, using Convolutional Neural Network (CNN). The demonstrations are made by successfully designing logic synthesis flows of three large scaled designs.
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