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Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...
"Tensor" is a reference to Google's TensorFlow and Tensor Processing Unit technologies, and the chip is developed by the Google Silicon team housed within the company's hardware division, led by vice president and general manager Phil Carmack alongside senior director Monika Gupta, [15] in conjunction with the Google Research division.
In the period 2015–2017 Google invented the Tensor Processing Unit (TPU). [39] TPUs are dedicated, fixed function hardware units that specialize in the matrix multiplications needed for tensor products. Specifically, they implement an array of 65,536 multiply units that can perform a 256x256 matrix sum-product in just one global instruction ...
Google's head of hardware Rick Osterloh explains how the company's first custom designed chip, Tensor, is all about AI.
Accelerators are used in cloud computing servers, including tensor processing units (TPU) in Google Cloud Platform [10] and Trainium and Inferentia chips in Amazon Web Services. [11] A number of vendor-specific terms exist for devices in this category, and it is an emerging technology without a dominant design.
The company has assembled a chip team of about 20 people, led by top engineers who have previously built Tensor Processing Units (TPUs) at Google, including Thomas Norrie and Richard Ho.
Groq was founded in 2016 by a group of former Google engineers, led by Jonathan Ross, one of the designers of the Tensor Processing Unit (TPU), an AI accelerator ASIC, and Douglas Wightman, an entrepreneur and former engineer at Google X (known as X Development), who served as the company’s first CEO.
In May 2016, Google announced its Tensor processing unit (TPU), an application-specific integrated circuit (ASIC, a hardware chip) built specifically for machine learning and tailored for TensorFlow. A TPU is a programmable AI accelerator designed to provide high throughput of low-precision arithmetic (e.g., 8-bit ), and oriented toward using ...