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SYSTEMS AND METHODS FOR HARNESSING ANALOG NOISE IN EFFICIENT OPTIMIZATION PROBLEM ACCELERATORS
SYSTEMS AND METHODS FOR HARNESSING ANALOG NOISE IN EFFICIENT OPTIMIZATION PROBLEM ACCELERATORS
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机译:高效优化问题加速器中模拟噪声的处理系统和方法
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摘要
Systems and methods are provided for implementing a hardware accelerator. The hardware accelerator emulates a neural network, and includes a memristor crossbar array, and a non-linear filter. The memristor crossbar array can be programmed to calculate node values of the neural network. The nodes values can be calculated in accordance with rules to reduce an energy function associated with the neural network. The non-linear filter is coupled to the memristor crossbar array and programmed to harness noise signals that may be present in analog circuitry of the hardware accelerator. The noise signals can be harnessed such that the energy function associated with the neural network converges towards a global minimum and modifies the calculated node values. In some embodiments, the non-liner filter is implemented as a Schmidt trigger comparator.
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