GEM: GPU-Accelerated Emulator-Inspired RTL Simulation

In this paper, we present a GPU-accelerated RTL simulator addressing critical challenges in high-speed circuit verification. Traditional CPU-based RTL simulators struggle with scalability and performance, and while FPGA-based emulators offer acceleration, they are costly and less accessible. Previous GPU-based attempts have failed to speed up RTL simulation due to the heterogeneous nature of circuit partitions, which conflicts with the SIMT (Single Instruction, Multiple Thread) paradigm of GPUs. Inspired by the design of emulators, our approach introduces a novel virtual Very Long Instruction Word (VLIW) architecture, designed for efficient CUDA execution. We also design a flow that maps circuit logic to the architecture in a process analogous to the FPGA CAD flow. This architecture mitigates issues of irregular memory access and thread divergence, unlocking GPU potential for RTL simulation. Our solution achieves up to $64 \times$ speed-up over the best CPU simulators, democratizing high-speed RTL simulation with accessible hardware and establishing a new frontier for GPUaccelerated circuit verification.

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Publication Details

Published
2025-06-22
DOI
https://doi.org/10.1109/dac63849.2025.11132713
Citations
2
Primary Topic
Simulation Techniques and Applications
Type
article
Field-Weighted Citation Impact
4.21
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article

GEM: GPU-Accelerated Emulator-Inspired RTL Simulation

Yibo Lin, Haoxing Ren, Zizheng Guo, Yanqing Zhang et al.
2 citations
Simulation Techniques and Applications
4.21
article

GEM: GPU-Accelerated Emulator-Inspired RTL Simulation

Yibo Lin, Haoxing Ren, Zizheng Guo, Yanqing Zhang, Runsheng Wang
article en
2 citations

Abstract

In this paper, we present a GPU-accelerated RTL simulator addressing critical challenges in high-speed circuit verification. Traditional CPU-based RTL simulators struggle with scalability and performance, and while FPGA-based emulators offer acceleration, they are costly and less accessible. Previous GPU-based attempts have failed to speed up RTL simulation due to the heterogeneous nature of circuit partitions, which conflicts with the SIMT (Single Instruction, Multiple Thread) paradigm of GPUs. Inspired by the design of emulators, our approach introduces a novel virtual Very Long Instruction Word (VLIW) architecture, designed for efficient CUDA execution. We also design a flow that maps circuit logic to the architecture in a process analogous to the FPGA CAD flow. This architecture mitigates issues of irregular memory access and thread divergence, unlocking GPU potential for RTL simulation. Our solution achieves up to $64 \times$ speed-up over the best CPU simulators, democratizing high-speed RTL simulation with accessible hardware and establishing a new frontier for GPUaccelerated circuit verification.

Peking University (CN), Nvidia (United States) (US)
Openalex Percentile: Top 5%
Simulation Techniques and Applications
4.21
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