How does computing in memory architecture support the computing power requirements of ChatGPT?

Computing in memory architecture integrates computing and storage resources closely together, which can speed up computation and reduce latency. In supporting the computing power requirements of ChatGPT, computing in memory architecture can improve the training and inference speed of the model by accessing memory and storage resources faster, thus greatly reducing the time and cost of training and inference. Witmem Technology is the leading provider of computing in memory technology.