Member-only story
What are TPUs: Google’s Powerhouse for AI?
Google is one of the most important players in the field of artificial intelligence, as its subsidiary, DeepMind, developed the AlphaGo program, which in 2016 beat the world champion in Go, a game renowned for its great complexity and strategic depth. Google has also developed the TensorFlow framework that enables researchers and developers to develop AI programs easily and efficiently.
Google goes beyond only developing the AI software, but has also developed new processing units known as TPUs to accelerate the training and inference process of large AI models that require a huge number of parallel calculations and consume a lot of energy when using traditional processing units such as GPU and CPU.
What are Google TPUs?
TPUs (Tensor Processing Units) are specialized chips designed to accelerate machine learning tasks, particularly those involving neural networks (deep learning). Their design prioritizes both speed and efficiency, aiming to complete the complex calculations required by AI models faster and with lower energy consumption. Initially developed for internal use at Google in 2015, TPUs became available for broader use through Google Cloud services in 2018. Since 2019, Google has also offered a smaller version of the TPU chip suitable for integration into edge devices.
