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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.
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 ...
Third-generation Tensor Cores with FP16, bfloat16, TensorFloat-32 (TF32) and FP64 support and sparsity acceleration. [9] The individual Tensor cores have with 256 FP16 FMA operations per clock 4x processing power (GA100 only, 2x on GA10x) compared to previous Tensor Core generations; the Tensor Core Count is reduced to one per SM.
Tensor cores: A tensor core is a unit that multiplies two 4×4 FP16 matrices, and then adds a third FP16 or FP32 matrix to the result by using fused multiply–add operations, and obtains an FP32 result that could be optionally demoted to an FP16 result. [12] Tensor cores are intended to speed up the training of neural networks. [12]
The M4 Pro features an up to 14-core CPU, with 10 performance cores and 4 efficiency cores, along with up to a 20-core GPU that Apple claims is twice as powerful as that in the M4 when used in the corresponding MacBook Pro. The M4 Pro is available with up to 64GB unified memory (Mac Mini) with a theoretical maximum bandwidth of 273GB/sec. [11]
NVDLA is available for product development as part of Nvidia's Jetson Xavier NX, a small circuit board in a form factor about the size of a credit card which includes a 6-core ARMv8.2 64-bit CPU, an integrated 384-core Volta GPU with 48 Tensor Cores, and dual NVDLA "engines", as described in their own press release. [4]
The Apple A18 and A18 Pro feature an Apple-designed 64-bit ARMv9.2-A six-core CPU with two high-performance cores and four energy-efficient cores, a five-core (A18) and six-core (A18 Pro) GPU and a NPU with 16 cores. Both are produced on TSMC N3E (3nm FinFET) and measure 90 mm 2 and 105 mm 2 respectively. [6]
Google Tensor is a series of ARM64-based system-on-chip (SoC) processors designed by Google for its Pixel devices. It was originally conceptualized in 2016, following the introduction of the first Pixel smartphone, though actual developmental work did not enter full swing until 2020.