公开(公告)号：US20190095796A1

公开(公告)日：2019-03-28

申请号：US15713573

申请日：2017-09-22

Applicant: INTEL CORPORATION

Inventor： LI CHEN ,  MICHAEL LEMAY ,  YE ZHUANG

IPC: G06N3/08 ,  G06F9/50

Abstract: Logic may determine a physical resource assignment via a neural network logic trained to determine an optimal policy for assignment of the physical resources in source code. Logic may generate training data to train a neural network by generating multiple instances of machine code for one or more source codes in accordance with different policies. Logic may generate different policies by adjusting, combining, mutating, and/or randomly changing a previous policy. Logic may execute and measure and/or statically determine measurements for each instance of a machine code associated with a source code to determine a reward associated with each state in the source code. Logic may apply weights and biases to the training data to approximate a value function. Logic may determine a gradient descent of the approximated value function and may backpropagate the output from the gradient descent to adjust the weights and biases to determine an optimal policy.