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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 ...
TPU or tpu may refer to: Science and technology. Tensor Processing Unit, a custom ASIC built by Google, tailored for their TensorFlow platform;
Simultaneous and heterogeneous multithreading (SHMT) is a software framework that takes advantage of heterogeneous computing systems that contain a mixture of central processing units (CPUs), graphics processing units (GPUs), and special purpose machine learning hardware, for example Tensor Processing Units (TPUs).
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 ...
2NF—second normal form; 3GL—third-generation programming language; 3GPP—3rd Generation Partnership Project – 3G comms; 3GPP2—3rd Generation Partnership Project 2; 3NF—third normal form; 386—Intel 80386 processor; 486—Intel 80486 processor; 4B5BLF—4-bit 5-bit local fiber; 4GL—fourth-generation programming language; 4NF ...
An AI accelerator, deep learning processor or neural processing unit (NPU) is a class of specialized hardware accelerator [1] or computer system [2] [3] designed to accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision.
An instruction set architecture (ISA) is an abstract model of a computer, also referred to as computer architecture.A realization of an ISA is called an implementation.An ISA permits multiple implementations that may vary in performance, physical size, and monetary cost (among other things); because the ISA serves as the interface between software and hardware.
Full-custom design is used for both ASIC design and for standard product design. The benefits of full-custom design include reduced area (and therefore recurring component cost), performance improvements, and also the ability to integrate analog components and other pre-designed —and thus fully verified—components, such as microprocessor ...