SeVeDo: Accelerating Transformer Inference with Optimized Quantization

This research paper introduces SeVeDo, a novel accelerator designed to improve the efficiency of Transformer-based models, focusing on low-bit inference. The hierarchical group quantization and SVD-guided mixed precision techniques are promising approaches for achieving higher performance and reduced resource consumption.