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Hyper-Parallel Superscalar Asynchronous RISC-V Processor Based on Event-Driven Logic

delete2025-12-15
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PRE
AI
K
Kangli Zhao
A
Anping He
J
Jun Ma
L
Lixin Zhang
L
Lixian Zhu
董群喜 (Qunxi Dong)
F
Fuze Tian
Q
Qingguo Zhou
Q
Qinglin Zhao
DOI:10.1109/TCSS.2025.3632912delete
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Abstract

Abstract

En 中文
Event-driven neuromorphic computing involves sparse and asynchronous signal activity, which leads to irregular computation patterns and fine-grained concurrency. As a result, processing architectures need to support both high parallelism and energy efficiency. Among existing architectural solutions, superscalar designs exhibit significant potential for addressing high parallelism demands. However, conventional superscalar processors, which rely on synchronous circuits, maintain high-frequency clocking at all times, leading to substantial power inefficiency in sparse computation scenarios. To address this issue, we propose an asynchronous superscalar architecture that replaces global clocking with fully local handshake-based control, implemented using a bundled-data asynchronous protocol. The design supports decoding of up to 64 scalar instructions per cycle and implements the RISC-V RV32IMC instruction set. A prototype was fabricated using a 110 nm complementary metal oxide semiconductor (CMOS) process and was evaluated through post-layout simulation. Operating at 1.2 V, the processor delivers a peak INT8 throughput of 669.4 GOPS, with a static power consumption of 421 mW.
Keywords:
Asynchronous superscalar architecture
instruction-level parallelism
neuromorphic computing
parallel computing
RISC-V

Journal

IEEE Transactions on Computational Social Systems cover
IEEE Transactions on Computational Social Systems
IF:
4.9
Papers:
577
Citations:
6.8K

Organization

L
Lanzhou University
Scholars:
1.1W
Papers: 3.2K
Citations: 3.8W
B
Beijing Institute of Technology
Scholars:
5.2K
Papers: 2.1K
Citations: 6.0W