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Surpassing Sycamore: Achieving Energetic Superiority Through System-Level Circuit Simulation
Conference proceeding

Surpassing Sycamore: Achieving Energetic Superiority Through System-Level Circuit Simulation

Rong Fu, Zhongling Su, Han-Sen Zhong, Xiti Zhao, Jianyang Zhang, Feng Pan, Pan Zhang, Xianhe Zhao, Ming-Cheng Chen, Chao-Yang Lu, …
Proceedings of the International Conference for High Performance Computing, Networking, Storage, and Analysis, pp.1-20
ACM Conferences
SC '24: The International Conference for High Performance Computing, Networking, Storage, and Analysis
17/11/2024
DOI: https://doi.org/10.1109/SC41406.2024.00085

Abstract

Computer systems organization Computer systems organization -- Architectures Computer systems organization -- Embedded and cyber-physical systems Computer systems organization -- Embedded and cyber-physical systems -- Embedded systems Computer systems organization -- Embedded and cyber-physical systems -- Embedded systems -- Embedded hardware Computer systems organization -- Embedded and cyber-physical systems -- System on a chip Computing methodologies Computing methodologies -- Distributed computing methodologies Computing methodologies -- Distributed computing methodologies -- Distributed algorithms Hardware Hardware -- Emerging technologies Hardware -- Emerging technologies -- Analysis and design of emerging devices and systems Hardware -- Emerging technologies -- Analysis and design of emerging devices and systems -- Emerging architectures Hardware -- Power and energy Hardware -- Power and energy -- Power estimation and optimization
In this paper, we present a groundbreaking largescale system technology that leverages optimization on global, node, and device levels to achieve unprecedented scalability for tensor networks. Our techniques enable accommodating largescale tensor networks with up to tens of terabytes of memory, reaching up to 2304 GPUs with a peak computing power of 561 PFLOPS. Notably, we have achieved a time-to-solution of 14.22 seconds with an energy consumption of 2.39 kWh which achieved a fidelity of 0.002. Our most remarkable result is a time-to-solution of 17.18 seconds, with energy consumption of only 0.29 kWh which achieved a XEB of 0.002 after post-processing. The experiments conducted demonstrate that our research outperforms Google's quantum processor Sycamore in both speed and energy efficiency, which recorded 600 seconds and 4.3 kWh, respectively. The code is available at https://github.com/DeepLinkorg/OpenTenNet.

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