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Computationally Efficient Low Power Neuron Model for Digital Brain

机译:用于数字大脑的计算有效的低功率神经元模型

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Modern supercomputers are capable of performing elementary operations of the order of petaflops. This power is comparable with the computational power of a human brain. The power supply required by supercomputers is in megawatts while human brain requires few watts to perform the same elementary operations as the modern supercomputers can. Thus the power consumption of supercomputers can be reduced (about 105 times) by considering the neuromorphic structure of a brain and attempt to mimic it on hardware chip to construct the computer that can function in the same manner as the human brain. In this paper we have proposed to develop the model for single brain cell, that can be replicated to built the whole brain model having computational power of supercomputers but the energy supply comparable with human brain.
机译:现代超级计算机能够执行petaflop级别的基本操作。该能力可与人脑的计算能力相媲美。超级计算机所需的电源以兆瓦为单位,而人脑只需几瓦即可执行与现代超级计算机相同的基本操作。因此,超级计算机的功耗可以降低(大约10 5 时代)来考虑大脑的神经形态结构,并尝试在硬件芯片上模仿它,以构建可以与人脑以相同方式工作的计算机。在本文中,我们提出了开发单脑细胞模型的方法,该模型可以复制以建立具有超级计算机的计算能力但能提供与人脑相当的能量的全脑模型。

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