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HiFi-LLP predictor accelerates HW-NAS with confidence metrics · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have developed HiFi-LLP, a novel latency predictor designed to accelerate hardware-aware neural architecture search (HW-NAS) for deep neural networks on edge devices. This predictor utilizes graph attention networks and incorporates a confidence metric to improve accuracy and reduce the need for extensive hardware-in-the-loop testing. HiFi-LLP demonstrates superior performance compared to existing platform-specific predictors, achieving high correlation and accuracy on the LatBench dataset. A hybrid NAS framework leverages HiFi-LLP's confidence scores to selectively use hardware feedback, leading to significant speedups in the search process while maintaining competitive results. AI

IMPACT Accelerates the deployment of deep neural networks on edge devices by improving the efficiency of hardware-aware optimization techniques.

RANK_REASON The cluster contains a research paper detailing a new method for latency prediction in hardware-aware neural architecture search.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

HiFi-LLP predictor accelerates HW-NAS with confidence metrics · 2 sources tracked

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The cluster contains a research paper detailing a new method for latency prediction in hardware-aware neural architecture search.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Shambhavi Balamuthu Sampath, Behzad Shomali, Nael Fasfous, Moritz Thoma, Judeson Anthony Fernando, Lukas Frickenstein, Pierpaolo Mori, Manoj Rohit Vemparala, Alexander Frickenstein, Walter Stechele ·

    HiFi-LLP: High-Fidelity, Low-Cost Latency Predictors with Confidence for Robust HW-NAS

    arXiv:2607.11746v1 Announce Type: new Abstract: With deep neural networks (DNNs) increasingly deployed on edge devices, hardware (HW)-aware optimization techniques--such as HW-aware compression and HW-aware neural architecture search (HW-NAS)--have become essential. These methods…

  2. arXiv cs.LG TIER_1 English(EN) · Walter Stechele ·

    HiFi-LLP: High-Fidelity, Low-Cost Latency Predictors with Confidence for Robust HW-NAS

    With deep neural networks (DNNs) increasingly deployed on edge devices, hardware (HW)-aware optimization techniques--such as HW-aware compression and HW-aware neural architecture search (HW-NAS)--have become essential. These methods rely on real feedback from the target hardware …

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