Accelerator Design

Accelerator design focuses on creating specialized hardware to efficiently execute computationally intensive tasks, particularly in machine learning and scientific computing. Current research emphasizes co-designing algorithms and accelerators for specific model architectures like Vision Transformers, Graph Convolutional Networks, and 3D Convolutional Neural Networks, often incorporating techniques like quantization and sparsity to improve performance and energy efficiency. These advancements are crucial for deploying complex models on resource-constrained devices (e.g., edge devices, mobile phones) and for accelerating large-scale scientific simulations, ultimately impacting various fields from robotics to particle physics.