#transformer-compression News & Analysis

2 articles tagged with #transformer-compression. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 17/10

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TRINE: A Token-Aware, Runtime-Adaptive FPGA Inference Engine for Multimodal AI

TRINE is a new FPGA accelerator and compiler that enables efficient end-to-end inference for multimodal AI models (combining vision transformers, CNNs, and language models) without requiring reconfiguration. The system achieves up to 22.57x latency reduction compared to RTX 4090 GPUs while consuming only 20-21W, demonstrating significant energy efficiency gains for embedded AI deployment.

AIBullisharXiv – CS AI · May 287/10

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GoQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization

GoQuant introduces Orthogonal Residual Projection (ORP), a quantization framework that enables efficient deployment of large language models on edge devices by replacing multiplication operations with bit-shifts. The approach achieves competitive performance at 3-bit precision while reducing calibration time to 15 minutes, addressing fundamental geometric limitations in power-of-two quantization.

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