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Task-specific AI accelerators

When the beam simulator is a 2D finite-element model, does a quantised surrogate (and an accelerator for it) pay?

research/accel-surrogate2d

When the beam simulator is a 2D plane-stress FE model, does a quantised MLP surrogate (and an accelerator) pay? The energy break-even is met (34x at 32x4 mesh, 319x at 64x8, assumed constants), and the surrogate's 2 % error against its FE is small beside the FE's own 9 % discretisation error; but the locking Q4 simulator is itself inaccurate. Stylised.

7 tests

What it found

The cantilever of accel-surrogate meshed as a 2D plane-stress continuum (bilinear quadrilaterals, 32×4 and 64×8 meshes). An 8-32-32-1 MLP imitates each solve and is quantised to 6 and 8 weight bits. With assumed energy constants the FE solve costs 34× (32×4) and 319× (64×8) the 8-bit MLP's energy, so the break-even that failed for the closed-form beam is met. Against a 128×16 reference mesh the 64×8 solve is itself off by a median 9.2 %, the float surrogate by 8.7 % and the 6-bit QAT surrogate by 9.2 %; the surrogate adds little beside the simulator's own error. Limitations: the locking Q4 elements make the simulator inaccurate, two meshes, three seeds, assumed energy model, no RTL. Stylised.

A figure from its own output

Figure produced by research/accel-surrogate2d: figure
accel-surrogate2d/experiments/figure.svg, written by the project's own experiment code.

Paper, code and results

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Produced with AI assistance (Claude). Results are from the code in this repository and are simulated or stylised unless the abstract says otherwise; nothing here implies affiliation with or endorsement by any lab, researcher or company cited. MIT licensed.