Overview
Google Cloud TPUs (Tensor Processing Units) are custom-designed ASICs (application-specific integrated circuits) built to accelerate machine learning workloads. TPUs optimize performance and cost for both AI model training and inference. They are integrated with Google Kubernetes Engine (GKE) and Vertex AI for scalable workload orchestration and a fully-managed AI platform experience. TPUs are designed to efficiently handle large matrix calculations, especially for large language models (LLMs) and recommendation models leveraging SparseCores. Different versions of TPUs are available, including Ironwood, Trillium, v5p, and v5e, each offering varying levels of performance and cost-effectiveness to address different AI workload needs. They provide seamless integration with leading AI frameworks like PyTorch, JAX, and TensorFlow.