Algorithm Hardware Co Design

Algorithm-hardware co-design optimizes both the software (algorithms) and hardware of computing systems for improved efficiency and performance in machine learning applications. Current research focuses on integrating specialized algorithms, such as spiking neural networks and transformers, with tailored hardware architectures like neuromorphic processors and FPGAs, often employing techniques like quantization and pruning to reduce computational demands. This interdisciplinary approach leads to significant advancements in energy efficiency and speed for various tasks, including computer vision, knowledge graph reasoning, and neural network inference, impacting both the development of more powerful AI systems and the design of energy-efficient edge devices.