Locus: A Framework for Exploring and Optimizing Point Addition Hardware for Zero-Knowledge Proofs
cs.AR, cs.CR
Submitted: 2026-09-16
Updated: 2026-09-16
Comments: 9 pages, 10 figures, 9 tables. Accepted at the IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2026)
Code: https://github.com/cryptolets/cryptolets
License: http://creativecommons.org/licenses/by/4.0/
The gist: Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving and verifiable computation, but their cryptographic primitives impose high computational overheads.
Terminology
Abstract
Zero-Knowledge Proofs (ZKPs) are critical for privacy-preserving and verifiable computation, but their cryptographic primitives impose high computational overheads. One such primitive is point addition (PADD) on elliptic curves. Several prior works have implemented PADDs in hardware, but only for a few specific elliptic curves and design points, leaving a large design space unexplored, and lacking systematic guidance on hardware design trade-offs. To address this gap, we present Locus, a framework dedicated to optimizing and exploring point addition hardware. Given the parameters of any elliptic curve in a supported equation form, Locus automatically generates ASIC and FPGA implementations of PADD, enabling systematic exploration of the PADD design space. Using Locus, we conduct the first comprehensive hardware-focused study of PADD designs, exploring trade-offs over 1,000 design points. On a 12nm technology node, our framework produces PADD designs that yield a 2.71 times geomean speedup and 3.11 times geomean area reduction compared to prior ASICs, 34.67 times geomean speedup over CPU, and 3.15 times geomean speedup on end-to-end proof generation when integrated into a prior ZKP accelerator at iso-area. Locus is available at https://github.com/cryptolets/cryptolets/tree/locus.
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