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arXiv · 2601.18140

RTeAAL Sim: Using Tensor Algebra to Represent and Accelerate RTL Simulation (Extended Version)

Yan Zhu·Boru Chen·Christopher W. Fletcher·Nandeeka Nayak
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Abstract

RTL simulation on CPUs remains a persistent bottleneck in hardware design. State-of-the-art simulators embed the circuit directly into the simulation binary, resulting in long compilation times and execution that is fundamentally CPU frontend-bound, with severe instruction-cache pressure. This work proposes RTeAAL Sim, which reformulates RTL simulation as a sparse tensor algebra problem. By representing RTL circuits as tensors and simulation as a sparse tensor algebra kernel, RTeAAL Sim decouples simulation behavior from binary size and makes RTL simulation amenable to well-studied tensor algebra optimizations. We demonstrate that a prototype of our tensor-based simulator, even with a subset of these optimizations, already mitigates the compilation overhead and frontend pressure and achieves performance competitive with the highly optimized Verilator simulator across multiple CPUs and ISAs.

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Yan Zhu, Boru Chen, Christopher W. Fletcher, Nandeeka Nayak. 2026-01-26. RTeAAL Sim: Using Tensor Algebra to Represent and Accelerate RTL Simulation (Extended Version). https://doi.org/10.1145/3779212.3790214

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