Vector extensions are designed to support complex arithmetic operations required for applications involving linear algebra, such as supercomputers, cryptography, AI, ML, and deep learning.
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The research work presented at IEDM 2019 measured a 5x reduction in energy use compared to an equivalent chip using formal coding. The neural network implementation is made such that synapses are placed close to neurons, which enables direct synaptic current integration.
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The Aetina Jetson TX2 4GB platform brings 1.3 TFLOPs of AI performance and 256 Nvidia CUDA cores. According to the company, the Jetson TX2 4GB has better price-performance-ratio than Jetson TX2, which reduces development expense on the same compute performance level.
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