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Graphics Processing Unit (GPU) vs Tensor Processing Unit (TPU) vs Field Programmable Gate Arrays (FPGA)

Graphics Processing Unit (GPU), Tensor Processing Unit (TPU) and Field Programmable Gate Array (FPGA) are processors with a specialized purpose and architecture. We have compared these in respect to Memory Subsystem Architecture, Compute Primitive, Performance, Purpose, Usage and Manufacturers.

tpu

What is Neural processing unit (NPU)?

A neural processing unit (NPU) is a microprocessor that specializes in the acceleration of machine learning algorithms. Examples include TPU by Google, NVDLA by Nvidia, EyeQ by Intel, Inferentia by Amazon, Ali-NPU by Alibaba, Kunlun by Baidu, Sophon by Bitmain, MLU by Cambricon, IPU by Graphcore

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Central Processing Unit (CPU) vs Graphics Processing Unit (GPU) vs Tensor Processing Unit (TPU)

Central Processing Unit (CPU), Graphics Processing Unit (GPU) and Tensor Processing Unit (TPU) are processors with a specialized purpose and architecture. We have compared these in respect to Memory Subsystem Architecture, Compute Primitive, Performance, Purpose, Usage and Manufacturers.

Machine Learning (ML)

Tensor Processing Unit (TPU) explained

A tensor processing unit (TPU) is a proprietary processor designed by Google in 2016 for use in neural networks inference. Norm Jouppi was the Technical leader of the TPU project. Key ideas in TPU include Matrix Multiplier Unit, Unified Buffer, Activation Unit and systolic array