tinyML Summit 2022: Mastering the 3 Pillars of AI Acceleration: Algorithms, Hardware and Software скачать в хорошем качестве

tinyML Summit 2022: Mastering the 3 Pillars of AI Acceleration: Algorithms, Hardware and Software

tinyML Summit 2022 tinyML Hardware Session Mastering the 3 Pillars of AI Acceleration: Algorithms, Hardware and Software Swagath VENKATARAMANI, Research Staff Member, IBM The success of Deep Neural Networks (DNNs) in performing complex AI tasks across many domains have been largely attributed to scale—the scale of the network, scale of the dataset of on which trained, among others. Hardware specialization and acceleration is regarded key to satiate the computational demands of DNNs, which requires synergistic cross-layer design across different layers of the compute stack. Guided by the evolution of AI workloads, this talk describes a holistic approach to designing specialized AI systems pioneered by IBM Research. This involves mastering the 3 key pillars of AI accelerator design: (i) approximate computing techniques to design low-precision DNNs models that maintain the same level of accuracy, (ii) hardware techniques to design scalable dense/sparse computational arrays that support a spectrum of precisions, and (iii) software methodologies to systematically map DNNs with diverse computational characteristics so as to extract maximum performance while simultaneously presenting intuitive (and familiar) programming and user interfaces.