Systems and methods for generating gaussian random numbers with hardware acceleration
AssigneeIntel Corporation
InventorsYiwen Guo, Anbang Yao, Dongqi Cai, Libin Wang, Lin Xu, Ping Hu, Shangong Wang, Wenhua Cheng
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Abstract
Described herein are hardware acceleration of random number generation for machine learning and deep learning applications. An apparatus (700) includes a uniform random number generator (URNG) circuit (710) to generate uniform random numbers and an adder circuit (750) that is coupled to the URNG circuit (710). The adder circuit hardware (750) accelerates generation of Gaussian random numbers for machine learning.
Claims20
An apparatus comprising:
- a uniform random number generator (URNG) circuit to generate uniform random numbers;
- and
- an adder circuit coupled to the URNG circuit, the adder circuit to hardware accelerate generation of Gaussian random numbers for machine learning.
A method for generating Gaussian random numbers comprising:
- utilizing a uniform random number generator (URNG) circuit to generate uniform random numbers;
- adding, with a first adder of an adder circuit, first and second uniform random numbers from the URNG circuit to generate a first output of the first adder;
- and
- adding, with a second adder of the adder circuit, a third uniform random number from the URNG circuit with the first output to generate a first output of the second adder.
At least one machine-readable medium comprising a plurality of instructions, executed on a computing device, to facilitate the computing device to perform one or more operations comprising:
- utilizing a uniform random number generator (URNG) circuit to generate uniform random numbers;
- adding, with a first adder of an adder circuit, first and second uniform random numbers from the URNG circuit to generate a first output of the first adder;
- and
- adding, with a second adder of the adder circuit, a third uniform random number from the URNG circuit with the first output to generate a first output of the second adder.
Dependencies are inferred from the claim text.