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公开(公告)号:US11741352B2
公开(公告)日:2023-08-29
申请号:US15242691
申请日:2016-08-22
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor: Tayfun Gokmen , Seyoung Kim , Dennis M. Newns , Yurii A. Vlasov
Abstract: A resistive processing unit (RPU) that includes a pair of transistors connected in series providing an update function for a weight of a training methodology to the RPU, and a read transistor for reading the weight of the training methodology. In some embodiments, the resistive processing unit (RPU) further includes a capacitor connecting a gate of the read transistor to the air of transistors providing the update function for the resistive processing unit (RPU). The capacitor stores said weight of training methodology for the RPU.
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公开(公告)号:US11520855B2
公开(公告)日:2022-12-06
申请号:US16874819
申请日:2020-05-15
Inventor: Lior Horesh , Oguzhan Murat Onen , Haim Avron , Tayfun Gokmen , Vasileios Kalantzis , Shashanka Ubaru
Abstract: A computer-implemented method is presented for performing matrix sketching by employing an analog crossbar architecture. The method includes low rank updating a first matrix for a first period of time, copying the first matrix into a dynamic correction computing device, switching to a second matrix to low rank update the second matrix for a second period of time, as the second matrix is low rank updated, feeding the first matrix with first stochastic pulses to reset the first matrix back to a first matrix symmetry point, copying the second matrix into the dynamic correction computing device, switching back to the first matrix to low rank update the first matrix for a third period of time, and as the first matrix is low rank updated, feeding the second matrix with second stochastic pulses to reset the second matrix back to a second matrix symmetry point.
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公开(公告)号:US20220327375A1
公开(公告)日:2022-10-13
申请号:US17226416
申请日:2021-04-09
Applicant: International Business Machines Corporation
Inventor: Tayfun Gokmen
Abstract: Embodiments disclosed herein include a method of training a DNN. A processor initializes an element of an A matrix. The element may include a resistive processing unit. A processor determines incremental weight updates by updating the element with activation values and error values from a weight matrix multiplied by a chopper value. A processor reads an update voltage from the element. A processor determines a chopper product by multiplying the update voltage by the chopper value. A processor stores an element of a hidden matrix. The element of the hidden matrix may include a summation of continuous iterations of the chopper product. A processor updates a corresponding element of a weight matrix based on the element of the hidden matrix reaching a threshold state.
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公开(公告)号:US11455520B2
公开(公告)日:2022-09-27
申请号:US16441831
申请日:2019-06-14
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor: Seyoung Kim , Tayfun Gokmen
Abstract: Methods and systems for copying weight values between weight arrays includes reading outputs from a first array and reading outputs from a second array. Differences between respective outputs of the first array and the second array are determined. Values of the second array are adjusted in accordance with the determined differences.
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公开(公告)号:US20220138579A1
公开(公告)日:2022-05-05
申请号:US17086856
申请日:2020-11-02
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor: Malte Johannes Rasch , Tayfun Gokmen
Abstract: A method is presented for artificial neural network training. The method includes storing weight values in an array of resistive processing unit (RPU) devices, wherein the array of RPU devices represents a weight matrix, defining the weight matrix to have an output dimension that is smaller than the input dimension such that the weight matrix has a rectangular configuration, and converting the weight matrix from a rectangular configuration to a more square-shaped configuration by repeating or concatenating the rectangular configuration of the weight matrix to increase a signal strength of a backward pass signal by copying an input of repeated weight elements during a forward cycle pass, summing output computations from the repeated weight elements, updating each of the repeated weight elements according to a backpropagated error or alternatively updating only one of the repeated weight elements by setting all forward values except one to zero during an update pass.
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公开(公告)号:US20200380349A1
公开(公告)日:2020-12-03
申请号:US16427598
申请日:2019-05-31
Applicant: International Business Machines Corporation
Inventor: Malte Rasch , Tayfun Gokmen
Abstract: Techniques for auto weight scaling a bounded weight range of RPU devices with the size of the array during ANN training are provided. In one aspect, a method of ANN training includes: initializing weight values winit in the array to a random value, wherein the array represents a weight matrix W with m rows and n columns; calculating a scaling factor β based on a size of the weight matrix W; providing digital inputs x to the array; dividing the digital inputs x by a noise and bound management factor α to obtain adjusted digital inputs x′; performing a matrix-vector multiplication of the adjusted digital inputs x′ with the array to obtain digital outputs y′; multiplying the digital outputs y′ by the noise and bound management factor α; and multiplying the digital outputs y′ by the scaling factor β to provide digital outputs y of the array.
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公开(公告)号:US20200380348A1
公开(公告)日:2020-12-03
申请号:US16427559
申请日:2019-05-31
Applicant: International Business Machines Corporation
Inventor: Malte Rasch , Tayfun Gokmen
Abstract: Advanced noise and signal management techniques for RPU arrays during ANN training are provided. In one aspect of the invention, a method for ANN training includes: providing an array of RPU devices with pre-normalizers and post-normalizers; computing and pre-normalizing a mean and standard deviation of all elements of an input vector x to the array that belong to the set group of each of the pre-normalizers; and computing and post-normalizing the mean p and the standard deviation a of all elements of an output vector y that belong to the set group of each of the post-normalizers.
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公开(公告)号:US10755170B2
公开(公告)日:2020-08-25
申请号:US15446264
申请日:2017-03-01
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor: Tayfun Gokmen , Rudolf M. Tromp
Abstract: A technique relates a resistive processing unit (RPU) array. A set of conductive column wires are configured to form cross-points at intersections between the set of conductive row wires and a set of conductive column wires. Two-terminal RPUs are hysteretic such that the two-terminal RPUs each have a conductance state defined by hysteresis, where a two-terminal RPU of the two-terminal RPUs is located at each of the cross-points.
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公开(公告)号:US10693736B2
公开(公告)日:2020-06-23
申请号:US14515563
申请日:2014-10-16
Applicant: International Business Machines Corporation
Inventor: Alain E. Biem , Bruce G. Elmegreen , Tayfun Gokmen
Abstract: A method for monitoring at least one simulation program includes capturing, by a computer, a plurality of simulation data from the at least one simulation program, the capturing is performed in real time while the at least one simulation program is continuously streaming the plurality of simulation data, analyzing, by the computer, the captured plurality of simulation data using a streaming data software, identifying a plurality of predefined criteria within the analyzed plurality of simulation data, the plurality of predefined criteria includes at least one of an event, a result and a variable, and providing feedback to the at least one simulation program to modify a plurality of simulation parameters according to the at least one identified event, result and variable.
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公开(公告)号:US20200044107A1
公开(公告)日:2020-02-06
申请号:US16595959
申请日:2019-10-08
Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
Inventor: Tayfun Gokmen , Oki Gunawan , Richard A. Haight , Jeehwan Kim , David B. Mitzi , Mark T. Winkler
IPC: H01L31/075 , H01L31/032 , H01L31/18 , H01L31/0328 , H01L31/077
Abstract: A photovoltaic device includes a first contact and a hybrid absorber layer. The hybrid absorber layer includes a chalcogenide layer and a semiconductor layer in contact with the chalcogenide layer. A buffer layer is formed on the absorber layer, and a transparent conductive contact layer is formed on the buffer layer.
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