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公开(公告)号：US20210157734A1
公开(公告)日：2021-05-27
申请号：US16953242
申请日：2020-11-19
Inventor： Byung Jo KIM , Joo Hyun LEE , Seong Min KIM , Ju-Yeob KIM , Jin Kyu KIM , Mi Young LEE
IPC: G06F12/0862 , G06F12/02 , G06F13/16 , G06N3/063
Abstract: A method for controlling a memory from which data is transferred to a neural network processor and an apparatus thereof are provided, the method including: generating prefetch information of data by using a blob descriptor and a reference prediction table after history information is input; reading the data in the memory based on the pre-fetch information and temporarily archiving read data in a prefetch buffer; and accessing next data in the memory based on the prefetch information and temporarily archiving the next data in the prefetch buffer after the data is transferred to the neural network from the prefetch buffer.
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公开(公告)号：US20200151568A1
公开(公告)日：2020-05-14
申请号：US16541275
申请日：2019-08-15
Inventor： Mi Young LEE , Byung Jo KIM , Seong Min KIM , Ju-Yeob KIM , Jin Kyu KIM , Joo Hyun LEE
Abstract: An embodiment of the present invention provides a quantization method for weights of a plurality of batch normalization layers, including: receiving a plurality of previously learned first weights of the plurality of batch normalization layers; obtaining first distribution information of the plurality of first weights; performing a first quantization on the plurality of first weights using the first distribution information to obtain a plurality of second weights; obtaining second distribution information of the plurality of second weights; and performing a second quantization on the plurality of second weights using the second distribution information to obtain a plurality of final weights, and thereby reducing an error that may occur when quantizing the weight of the batch normalization layer.
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公开(公告)号：US20180211165A1
公开(公告)日：2018-07-26
申请号：US15828153
申请日：2017-11-30
Inventor： Kwang IL OH , Sung Eun KIM , Seong Mo PARK , Hyung-IL PARK , Joo Hyun LEE
CPC classification number: G06N3/08 , G06N3/04 , G06N3/063 , H03K3/017 , H03K3/0315 , H03K21/026
Abstract: Provided is a neuromorphic arithmetic device. The neuromorphic arithmetic device may include a synapse circuit, a metal line having an inherent capacitance component, an oscillator, a comparator, and a capacitance calibrator. The synapse circuit may be configured to perform a multiplication operation on a PWM signal and a weight to generate a current. The metal line may include a metal line capacitor in which a charge of the current is stored. The oscillator generates a plurality of pulses on the basis of the charge stored in the metal line capacitor. The comparator may compare a frequency of the plurality of pulses and a target frequency, and may generate a control signal on the basis of a result of the comparison. The capacitance calibrator may adjust a capacitance value of the metal line capacitor on the basis of the control signal.
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公开(公告)号：US20200174751A1
公开(公告)日：2020-06-04
申请号：US16695509
申请日：2019-11-26
Inventor： Min-Hyung CHO , Young-deuk JEON , Ki Hyuk PARK , Joo Hyun LEE
Abstract: The neuromorphic arithmetic device performs a multiply-accumulate (MAC) calculation using a multiplier and an accumulator. The neuromorphic arithmetic device includes an offset accumulator configured to receive a plurality of offset data measured a plurality of times and accumulate the plurality of offset data, a bit extractor configured to obtain average offset data by extracting at least one first bit from the plurality of accumulated offset data, and a cumulative synapse array configured to accumulate a plurality of multiplication values generated by the multiplier and output a cumulative result of the plurality of multiplication values corrected according to the average offset data.
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公开(公告)号：US20210357753A1
公开(公告)日：2021-11-18
申请号：US17317607
申请日：2021-05-11
Inventor： Jin Kyu KIM , Byung Jo KIM , Seong Min KIM , Ju-Yeob KIM , Ki Hyuk PARK , Mi Young LEE , Joo Hyun LEE , Young-deuk JEON , Min-Hyung CHO
Abstract: A method and apparatus for multi-level stepwise quantization for neural network are provided. The apparatus sets a reference level by selecting a value from among values of parameters of the neural network in a direction from a high value equal to or greater than a predetermined value to a lower value, and performs learning based on the reference level. The setting of a reference level and the performing of learning are iteratively performed until the result of the reference level learning satisfies a predetermined value and there is no variable parameter that is updated during learning among the parameters.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20200327390A1
公开(公告)日：2020-10-15
申请号：US16808124
申请日：2020-03-03
Inventor： Mi Young LEE , Joo Hyun LEE
Abstract: Provided is a method of operating a neural network computing device that is configured to communicate with an external memory device and execute a plurality of layers. The method includes computing a first input address, based on first layer information of a first layer among the plurality of layers and a first memory management table, and updating the first memory management table to generate a second memory management table, reading first input data to be input to the first layer from the external memory device, based on the computed first input address, computing a first output address, based on the first layer information and the second memory management table, and updating the second memory management table to generate a third memory management table, and storing first output data output from the first layer, based on the first output address, in the external memory device.
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公开(公告)号：US20180268571A1
公开(公告)日：2018-09-20
申请号：US15698499
申请日：2017-09-07
Inventor： Seong Mo PARK , Sung Eun KIM , Ju-Yeob KIM , Jin Kyu KIM , Kwang Il OH , Joo Hyun LEE
CPC classification number: G06T9/002 , G06T7/11 , G06T7/194 , G06T2200/28 , G06T2207/20081 , G06T2207/20084
Abstract: Provided is an image compression device including an object extracting unit configured to perform convolution neural network (CNN) training and identify an object from an image received externally, a parameter adjusting unit configured to adjust a quantization parameter of a region in which the identified object is included in the image on the basis of the identified object, and an image compression unit configured to compress the image on the basis of the adjusted quantization parameter.
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公开(公告)号：US20180204110A1
公开(公告)日：2018-07-19
申请号：US15867601
申请日：2018-01-10
Inventor： Byung Jo KIM , Joo Hyun LEE
IPC: G06N3/04
CPC classification number: G06N3/04 , G06N3/0454 , G06N3/063 , G06N3/082
Abstract: Provided is a design method of a compressed neural network system. The method includes generating a compressed neural network based on an original neural network model, analyzing a sparse weight among kernel parameters of the compressed neural network, calculating a maximum possible calculation throughput on a target hardware platform according to a sparse property of the sparse weight, calculating a calculation throughput with respect to access to an external memory on the target hardware platform according to the sparse property, and determining a design parameter on the target hardware platform by referring the maximum possible calculation throughput and the calculation throughput with respect to access.
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9.发明申请公开(公告)号：US20180096249A1
公开(公告)日：2018-04-05
申请号：US15718912
申请日：2017-09-28
Inventor： Jin Kyu KIM , Joo Hyun LEE
IPC: G06N3/08
CPC classification number: G06N3/082 , G06N3/0454
Abstract: Provided is a method for operating a convolutional neural network. The method includes performing learning on weights between neural network nodes by using input data, removing an adaptive parameter that performs learning using the input data after removing a weight having a size less than a threshold value among weights, and mapping remaining weights in the removing of the adaptive parameter to a plurality of representative values.
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公开(公告)号：US20210151091A1
公开(公告)日：2021-05-20
申请号：US16997445
申请日：2020-08-19
Inventor： Young-deuk JEON , Seong Min KIM , Jin Kyu KIM , Joo Hyun LEE , Min-Hyung CHO , Jin Ho HAN
IPC: G11C11/4076 , G11C11/4099 , G11C11/4096
Abstract: Disclosed are a device and a method for calibrating a reference voltage. The reference voltage calibrating device includes a data signal communication unit that transmits/receives a data signal, a data strobe signal receiving unit that receives a first data strobe signal and a second data strobe signal, a voltage level of the second data strobe signal being opposite to a voltage level of the first data strobe signal, and a reference voltage generating unit that sets a reference voltage for determining a data value of the data signal, based on the first data strobe signal and the second data strobe signal, and the reference voltage generating unit adjusts the reference voltage based on the first data strobe signal and the second data strobe signal.
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