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

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Zhu, Yan, Chen, Boru, Fletcher, Christopher W., Nayak, Nandeeka
Format: Preprint
Published: 2026
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914280317648896
author Zhu, Yan
Chen, Boru
Fletcher, Christopher W.
Nayak, Nandeeka
author_facet Zhu, Yan
Chen, Boru
Fletcher, Christopher W.
Nayak, Nandeeka
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2601_18140
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle RTeAAL Sim: Using Tensor Algebra to Represent and Accelerate RTL Simulation (Extended Version)
Zhu, Yan
Chen, Boru
Fletcher, Christopher W.
Nayak, Nandeeka
Hardware Architecture
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.
title RTeAAL Sim: Using Tensor Algebra to Represent and Accelerate RTL Simulation (Extended Version)
topic Hardware Architecture
url https://arxiv.org/abs/2601.18140