计算机科学
数据流
零知识证明
加速
密码学
计算
密码原语
并行计算
分布式计算
嵌入式系统
理论计算机科学
密码协议
算法
作者
Ye Zhang,Shuo Wang,Xian Zhang,Jiangbin Dong,Xingzhong Mao,Fan Long,Cong Wang,Dong Zhou,Mingyu Gao,Guangyu Sun
出处
期刊:International Symposium on Computer Architecture
日期:2021-06-01
被引量:18
标识
DOI:10.1109/isca52012.2021.00040
摘要
Zero-knowledge proof (ZKP) is a promising cryptographic protocol for both computation integrity and privacy. It can be used in many privacy-preserving applications including verifiable cloud outsourcing and blockchains. The major obstacle of using ZKP in practice is its time-consuming step for proof generation, which consists of large-size polynomial computations and multi-scalar multiplications on elliptic curves. To efficiently and practically support ZKP in real-world applications, we propose PipeZK, a pipelined accelerator with two subsystems to handle the aforementioned two intensive compute tasks, respectively. The first subsystem uses a novel dataflow to decompose large kernels into smaller ones that execute on bandwidth-efficient hardware modules, with optimized off-chip memory accesses and on-chip compute resources. The second subsystem adopts a lightweight dynamic work dispatch mechanism to share the heavy processing units, with minimized resource underutilization and load imbalance. When evaluated in 28 nm, PipeZK can achieve 10x speedup on standard cryptographic benchmarks, and 5x on a widely-used cryptocurrency application, Zcash.
科研通智能强力驱动
Strongly Powered by AbleSci AI