The paper compiles hardware-software co-design techniques including mixed-precision quantization, structural pruning, speculative decoding, and transformer accelerators to speed up multimodal foundation models, with examples in medical and code tasks.
Advancing healthcare in low-resource environments through an optimization and deployment framework for medical mul- timodal large language models,
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Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models
The paper compiles hardware-software co-design techniques including mixed-precision quantization, structural pruning, speculative decoding, and transformer accelerators to speed up multimodal foundation models, with examples in medical and code tasks.