Lazy Arithmetic using Systolic Arrays for Closing the Verification Gap on Embedded Systems
Complex algorithms such as deep neural networks are increasingly being deployed on embedded, resource constrained platforms. However, existing hardware and software schemes for implementing these models on the edge fall short, particularly for safety-critical applications such as medical devices. First, hardware such as GPUs, NPUs and TPUs are designed for throughput rather than correctness of computation of security, and are as such susceptible to fault injection attacks. Second, software schemes designed for porting algorithms onto edge devices -- such as quantization schemes -- are either static and sound (non-optimal power consumption), or dynamic yet unsound (non-optimal for safety-c...
| Authors | Taisa Kushner, Ryan McCleeary, Martin Brain |
|---|---|
| Primary category | cs.CR |
| Published | 16 July 2026 |
| Last updated at source | 16 July 2026 |
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