Property-driven Automatic Generation of Reduced-ISA Hardware

Nathan Bleier, John Sartori, Rakesh Kumar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


As the diversity of computing workloads and customers continues to increase, so does the need to customize hardware at low cost for different computing needs. This work focuses on automatic customization of a given hardware, available as a soft or firm IP, through eliminating unneeded or undesired instruction set architecture (ISA) instructions. We present a property-based framework for automatically generating reduced-ISA hardware. Our framework directly operates on a given arbitrary RTL or gate-level netlist, uses property checking to identify gates that are guaranteed to not toggle if only a reduced ISA needs to be supported, and automatically eliminates these untoggleable gates to generate a new design. We show a 14% gate count reduction when the Ibex [19] core is optimized using our framework for the instructions required by a set of embedded (MiBench) workloads. Reduced-ISA versions generated by our framework that support a limited set of ISA extensions and which cannot be generated using Ibex's parameterization options provide 10%47% gate count reduction. For an obfuscated Cortex M0 netlist optimized to support the instructions in the MiBench benchmarks, we observe a 20% area reduction and 18% gate count reduction compared to the baseline core, demonstrating applicability of our framework to obfuscated designs. We demonstrate the scalability of our approach by applying our framework to a 100,000-gate RIDECORE [21] design, showing a 14%17% gate count reduction.

Original languageEnglish (US)
Title of host publication2021 58th ACM/IEEE Design Automation Conference, DAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665432740
StatePublished - Dec 5 2021
Event58th ACM/IEEE Design Automation Conference, DAC 2021 - San Francisco, United States
Duration: Dec 5 2021Dec 9 2021

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X


Conference58th ACM/IEEE Design Automation Conference, DAC 2021
Country/TerritoryUnited States
CitySan Francisco

Bibliographical note

Publisher Copyright:
© 2021 IEEE.


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