Software Deployment
Software deployment encompasses the process of releasing and integrating software into operational environments, aiming for efficient, reliable, and secure execution. Current research emphasizes optimizing models for diverse hardware constraints (e.g., low-power wearables, microcontrollers), employing techniques like neural architecture search, quantization, and sparsity to improve performance and reduce resource consumption. This field is crucial for advancing AI applications across various domains, from autonomous vehicles and robotics to healthcare and industrial automation, by ensuring that sophisticated models can be effectively and reliably deployed in real-world settings.
Papers
Optimizing the Deployment of Tiny Transformers on Low-Power MCUs
Victor J. B. Jung, Alessio Burrello, Moritz Scherer, Francesco Conti, Luca Benini
CMULAB: An Open-Source Framework for Training and Deployment of Natural Language Processing Models
Zaid Sheikh, Antonios Anastasopoulos, Shruti Rijhwani, Lindia Tjuatja, Robbie Jimerson, Graham Neubig