PERFORMING MATRIX MULTIPLICATION IN HARDWARE
    51.
    发明申请

    公开(公告)号:US20200257754A1

    公开(公告)日:2020-08-13

    申请号:US16826075

    申请日:2020-03-20

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for performing a matrix multiplication using a hardware circuit are described. An example method begins by obtaining an input activation value and a weight input value in a first floating point format. The input activation value and the weight input value are multiplied to generate a product value in a second floating point format that has higher precision than the first floating point format. A partial sum value is obtained in a third floating point format that has a higher precision than the first floating point format. The partial sum value and the product value are combined to generate an updated partial sum value that has the third floating point format.

    VECTOR PROCESSING UNIT
    52.
    发明申请

    公开(公告)号:US20200233663A1

    公开(公告)日:2020-07-23

    申请号:US16843015

    申请日:2020-04-08

    Applicant: Google LLC

    Abstract: A vector processing unit is described, and includes processor units that each include multiple processing resources. The processor units are each configured to perform arithmetic operations associated with vectorized computations. The vector processing unit includes a vector memory in data communication with each of the processor units and their respective processing resources. The vector memory includes memory banks configured to store data used by each of the processor units to perform the arithmetic operations. The processor units and the vector memory are tightly coupled within an area of the vector processing unit such that data communications are exchanged at a high bandwidth based on the placement of respective processor units relative to one another, and based on the placement of the vector memory relative to each processor unit.

    LOW LATENCY MATRIX MULTIPLY UNIT
    53.
    发明申请

    公开(公告)号:US20200226202A1

    公开(公告)日:2020-07-16

    申请号:US16830894

    申请日:2020-03-26

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for a matrix multiply unit implemented as a systolic array of cells are disclosed. The matrix multiply unit may include cells arranged in columns of the systolic array. Two chains of weight shift registers per column of the systolic array are in the matrix multiply unit. Each weight shift register is connected to only one chain and each cell is connected to only one weight shift register. A weight matrix register per cell is configured to store a weight input received from a weight shift register. A multiply unit is coupled to the weight matrix register and configured to multiply the weight input of the weight matrix register with a vector data input in order to obtain a multiplication result.

    PERMUTING IN A MATRIX-VECTOR PROCESSOR
    54.
    发明申请

    公开(公告)号:US20190258694A1

    公开(公告)日:2019-08-22

    申请号:US16283913

    申请日:2019-02-25

    Applicant: Google LLC

    Abstract: A circuit comprises an input register configured to receive an input vector of elements, a control register configured to receive a control vector of elements, wherein each element of the control vector corresponds to a respective element of the input vector, and wherein each element specifies a permutation of a corresponding element of the input vector, and a permute execution circuit configured to generate an output vector of elements corresponding to a permutation of the input vector. Generating each element of the output vector comprises accessing, at the input register, a particular element of the input vector, accessing, at the control register, a particular element of the control vector corresponding to the particular element of the input vector, and outputting the particular element of the input vector as an element at a particular position of the output vector that is selected based on the particular element of the control vector.

    Accessing data in multi-dimensional tensors

    公开(公告)号:US10228947B2

    公开(公告)日:2019-03-12

    申请号:US15844192

    申请日:2017-12-15

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including an apparatus for processing an instruction for accessing a N-dimensional tensor, the apparatus including multiple tensor index elements and multiple dimension multiplier elements, where each of the dimension multiplier elements has a corresponding tensor index element. The apparatus includes one or more processors configured to obtain an instruction to access a particular element of a N-dimensional tensor, where the N-dimensional tensor has multiple elements arranged across each of the N dimensions, and where N is an integer that is equal to or greater than one; determine, using one or more tensor index elements of the multiple tensor index elements and one or more dimension multiplier elements of the multiple dimension multiplier elements, an address of the particular element; and output data indicating the determined address for accessing the particular element of the N-dimensional tensor.

    Permuting in a matrix-vector processor

    公开(公告)号:US10216705B2

    公开(公告)日:2019-02-26

    申请号:US15966275

    申请日:2018-04-30

    Applicant: Google LLC

    Abstract: A circuit comprises an input register configured to receive an input vector of elements, a control register configured to receive a control vector of elements, wherein each element of the control vector corresponds to a respective element of the input vector, and wherein each element specifies a permutation of a corresponding element of the input vector, and a permute execution circuit configured to generate an output vector of elements corresponding to a permutation of the input vector. Generating each element of the output vector comprises accessing, at the input register, a particular element of the input vector, accessing, at the control register, a particular element of the control vector corresponding to the particular element of the input vector, and outputting the particular element of the input vector as an element at a particular position of the output vector that is selected based on the particular element of the control vector.

    Permuting in a matrix-vector processor

    公开(公告)号:US09959247B1

    公开(公告)日:2018-05-01

    申请号:US15496418

    申请日:2017-04-25

    Applicant: Google LLC

    CPC classification number: G06F17/16 G06F7/76 G06F9/30032 G06F9/30036

    Abstract: A circuit comprises an input register configured to receive an input vector of elements, a control register configured to receive a control vector of elements, wherein each element of the control vector corresponds to a respective element of the input vector, and wherein each element specifies a permutation of a corresponding element of the input vector, and a permute execution circuit configured to generate an output vector of elements corresponding to a permutation of the input vector. Generating each element of the output vector comprises accessing, at the input register, a particular element of the input vector, accessing, at the control register, a particular element of the control vector corresponding to the particular element of the input vector, and outputting the particular element of the input vector as an element at a particular position of the output vector that is selected based on the particular element of the control vector.

    PERFORMING MATRIX MULTIPLICATION IN HARDWARE

    公开(公告)号:US20240370526A1

    公开(公告)日:2024-11-07

    申请号:US18638285

    申请日:2024-04-17

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for performing a matrix multiplication using a hardware circuit are described. An example method begins by obtaining an input activation value and a weight input value in a first floating point format. The input activation value and the weight input value are multiplied to generate a product value in a second floating point format that has higher precision than the first floating point format. A partial sum value is obtained in a third floating point format that has a higher precision than the first floating point format. The partial sum value and the product value are combined to generate an updated partial sum value that has the third floating point format.

    LOW LATENCY MATRIX MULTIPLY UNIT
    59.
    发明公开

    公开(公告)号:US20240362298A1

    公开(公告)日:2024-10-31

    申请号:US18638469

    申请日:2024-04-17

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for a matrix multiply unit implemented as a systolic array of cells are disclosed. The matrix multiply unit may include cells arranged in columns of the systolic array. Two chains of weight shift registers per column of the systolic array are in the matrix multiply unit. Each weight shift register is connected to only one chain and each cell is connected to only one weight shift register. A weight matrix register per cell is configured to store a weight input received from a weight shift register. A multiply unit is coupled to the weight matrix register and configured to multiply the weight input of the weight matrix register with a vector data input in order to obtain a multiplication result.

    LOW LATENCY MATRIX MULTIPLY UNIT
    60.
    发明公开

    公开(公告)号:US20240303297A1

    公开(公告)日:2024-09-12

    申请号:US18444249

    申请日:2024-02-16

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus for a matrix multiply unit implemented as a systolic array of cells are disclosed. Each cell of the matrix multiply includes: a weight matrix register configured to receive a weight input from either a transposed or a non-transposed weight shift register; a transposed weight shift register configured to receive a weight input from a horizontal direction to be stored in the weight matrix register; a non-transposed weight shift register configured to receive a weight input from a vertical direction to be stored in the weight matrix register; and a multiply unit that is coupled to the weight matrix register and configured to multiply the weight input of the weight matrix register with a vector data input in order to obtain a multiplication result.

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