Paper-Conference

Massive Spikes in LLMs are Bias Vectors: Mechanistic Uncovering and Spike-Free Quantization

Massive activation spikes in Large Language Models (LLMs) severely degrade quantization by stretching dynamic ranges. While prior hypotheses characterize these as high-level scalar …

Yung-Chin-Chen
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Optimizing Compute Core Assignment for Dynamic Batch Inference in AI Inference Accelerator

Modern AI inference accelerators offer high-performance and power-efficient computations for machine learning models. Most accelerators employ static inference to enhance …

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Ze-Wei Liou
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Design of Analog-AI Hardware Accelerators for Transformer-based Language Models

Analog Non-Volatile Memory-based accelerators offer high-throughput and energy-efficient Multiply-Accumulate operations for the large Fully-Connected layers that dominate …

G.-W.-Burr
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