From square to cube: Hardware processing for AI goes 3D, boosting processing power
In a paper published in Nature Photonics, researchers from the University of Oxford, along with collaborators from the Universities of Muenster, Heidelberg, and Exeter, report on their development of integrated photonic-electronic hardware capable of processing three-dimensional (3D) data, substantially boosting data processing parallelism for AI tasks.
The emergence of AI has profoundly transformed numerous industries. Driven by deep learning technology and Big Data, AI requires significant processing power for training its models. While the existing AI infrastructure relies on graphical processing units (GPUs), the substantial processing demands and energy expenses associated with its operation remain key…
Scientists introduce what they call 'simultaneous and heterogeneous multithreading' or SHMT. This system doubles computer processing speeds with existing hardware by simultaneously using graphics processing units (GPUs), hardware accelerators for artificial intelligence (AI) and machine learning (ML), or digital signal processing units to process information.