EFFICIENT DATA PROCESSING, ARBITRATION AND PRIORITIZATION

    公开(公告)号:US20240248764A1

    公开(公告)日:2024-07-25

    申请号:US18316602

    申请日:2023-05-12

    Applicant: Arm Limited

    CPC classification number: G06F9/5038 G06F9/505 G06F2209/5021

    Abstract: A memory unit configured for handling task data, the task data describing a task to be executed as a directed acyclic graph of operations, wherein each operation maps to a corresponding execution unit, and wherein each connection between operations in the acyclic graph maps to a corresponding storage element of the execution unit. The task data defines an operation space representing the dimensions of a multi-dimensional arrangement of the connected operations to be executed represented by the data blocks; the memory unit configured to receive a sequence of processing requests comprising the one or more data blocks with each data block assigned a priority value and comprising a block command. The memory unit is configured to arbitrate between the data blocks based upon the priority value and block command to prioritize the sequence of processing requests and wherein the processing requests include writing data to, or reading data from storage.

    TRACKING BUFFER REDUCTION AND REUSE IN A PROCESSOR

    公开(公告)号:US20240248755A1

    公开(公告)日:2024-07-25

    申请号:US18099595

    申请日:2023-01-20

    Applicant: Arm Limited

    CPC classification number: G06F9/4881 G06F9/3555

    Abstract: A processor comprising: a handling unit; a plurality of components each configured to execute a function. The handling unit can receive a task comprising operations on data in a coordinate space having N dimensions, receive a data structure describing execution of the task and comprising a partially ordered set of data items each associated with instructions usable by the plurality of components when executing the task, each data item is associated with a component among the plurality of components, each data item indicates dimensions of the coordinates space for which changes of coordinate causes the function of the associated component to execute, and dimensions of the coordinate space for which changes of coordinate causes the function of the associated component to store data ready to be used by another component. The handling unit iterates over the coordinate space and executes the task using the partially ordered set of data items.

    READING DATA WITHIN A COMPRESSED DATA STREAM

    公开(公告)号:US20240248754A1

    公开(公告)日:2024-07-25

    申请号:US18099594

    申请日:2023-01-20

    Applicant: Arm Limited

    CPC classification number: G06F9/4881

    Abstract: A processor to generate position data indicative of a position within a compressed data stream, wherein, previously, in executing a task, data of the compressed data stream ending at the position has been read by the processor from storage storing the compressed data stream. After reading the data, the processor reads further data of the compressed data stream from the storage, in executing the task, the further data located beyond the position within the compressed data stream. After reading the further data, the processor reads, based on the position data, a portion of the compressed data stream from the storage, in executing the task, starting from the position within the compressed data stream. The processor decompresses the portion of the compressed data stream to generate decompressed data, in executing the task.

    DATA STORAGE
    4.
    发明公开
    DATA STORAGE 审中-公开

    公开(公告)号:US20240193089A1

    公开(公告)日:2024-06-13

    申请号:US18063478

    申请日:2022-12-08

    Applicant: Arm Limited

    Abstract: A processor comprising a first storage managed as a circular buffer to store a plurality of data structures. Each data structure comprises: an identifier, a size indicator and first data associated with instructions for execution of a task. The processor is configured for searching for a data structure in the first storage. A data structure subsequent to the tail data structure can be located using a storage address in the first storage of a tail data structure and the size indicator of all data structures preceding the second data structure among the plurality of data structures. When a data structure is found, the task may be executed based at least in part on the first data of the found data structure.

    DATA STORAGE
    5.
    发明公开
    DATA STORAGE 审中-公开

    公开(公告)号:US20240126602A1

    公开(公告)日:2024-04-18

    申请号:US17967297

    申请日:2022-10-17

    Applicant: Arm Limited

    CPC classification number: G06F9/5016

    Abstract: A processor to execute a plurality of tasks comprising a first task and a second task. At least a part of the first task is to be executed simultaneously with at least a part of the second task. The processor comprises a handling unit to: determine an available portion of a storage available during execution of the part of the first task; determine a mapping between at least one logical address associated with data associated with the part of the second task and a corresponding at least one physical address of the storage corresponding to the available portion; and identify, based on the mapping, the at least one physical address corresponding to the at least one logical address associated with the data, for storing the data in the available portion of the storage.

    DATA ACCUMULATION
    6.
    发明公开
    DATA ACCUMULATION 审中-公开

    公开(公告)号:US20240248621A1

    公开(公告)日:2024-07-25

    申请号:US18099627

    申请日:2023-01-20

    Applicant: Arm Limited

    CPC classification number: G06F3/0626 G06F3/0644 G06F3/0673 G06F7/52

    Abstract: A processor to generate accumulated data comprising, for an operation cycle: performing an operation on a first bit range of a set of first input data to generate a set of operation data, which is accumulated with stored data within a first storage device. A lowest n bits of the accumulated data are accumulated with first further stored data within a first bit range of a second storage device, and are bit-shifted from the first storage device. Further accumulated data is generated, comprising, for an operation cycle: performing the operation on a second bit range of the set of first input data to generate a further set of operation data, which is accumulated with the stored data within the first storage device. A lowest m bits of the further accumulated data is accumulated with second further stored data within a second bit range of the second storage device.

    NEURAL PROCESSING FILTER
    7.
    发明申请

    公开(公告)号:US20210304378A1

    公开(公告)日:2021-09-30

    申请号:US16836440

    申请日:2020-03-31

    Applicant: Arm Limited

    Abstract: A computer-implemented method of providing a filter (F) in a neural processing unit comprises: receiving input corresponding to target dimensions (XT, YT) of the filter; receiving input corresponding to sub-filter dimensions (X1 . . . n′, Y1 . . . n′) of each of a plurality of sub-filters (SF1 . . . n) implementable in the neural processing unit; and defining the filter (F) as a combination of the plurality of sub-filters (SF1 . . . n), the combination having dimensions that equate to the target dimensions (XT, YT), and wherein the sub-filter dimensions (X1 . . . n′, Y1 . . . n′) of at least two of the sub-filters in the combination are unequal.

    COMPRESSION OF NEURAL NETWORK ACTIVATION DATA

    公开(公告)号:US20210027148A1

    公开(公告)日:2021-01-28

    申请号:US16518444

    申请日:2019-07-22

    Applicant: Arm Limited

    Abstract: A processor arranged to compress neural network activation data comprising an input module for obtaining neural network activation data. The processor also comprises a block creation module arranged to split the neural network activation data into a plurality of blocks; and a metadata generation module for generating metadata associated with at least one of the plurality of blocks. Based on the metadata generated a selection module selects a compression scheme for each of the plurality of blocks, and a compression module for applying the selected compression scheme to the corresponding block to produce compressed neural network activation data. An output module is also provided for outputting the compressed neural network activation data.

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