Virtually Padding Data Structures
    4.
    发明公开

    公开(公告)号:US20240069915A1

    公开(公告)日:2024-02-29

    申请号:US17899231

    申请日:2022-08-30

    CPC classification number: G06F9/30036 G06F12/10 G06F16/2237

    Abstract: A virtual padding unit provides a virtual padded data structure (e.g., virtually padded matrix) that provides output values for a padded data structure without storing all of the padding elements in memory. When the virtual padding unit receives a virtual memory address of a location in the virtual padded data structure, the virtual padding unit checks whether the location is a non-padded location in the virtual padded data structure or a padded location in the virtual padded data structure. If the location is a padded location in the virtual padded data structure, the virtual padding unit outputs a padding value rather than a value stored in the virtual padded data structure. If the location is a non-padded location in the virtual padded data structure, a value stored at the location is output.

    Virtually padding data structures

    公开(公告)号:US12118354B2

    公开(公告)日:2024-10-15

    申请号:US17899231

    申请日:2022-08-30

    CPC classification number: G06F9/30036 G06F12/10 G06F16/2237

    Abstract: A virtual padding unit provides a virtual padded data structure (e.g., virtually padded matrix) that provides output values for a padded data structure without storing all of the padding elements in memory. When the virtual padding unit receives a virtual memory address of a location in the virtual padded data structure, the virtual padding unit checks whether the location is a non-padded location in the virtual padded data structure or a padded location in the virtual padded data structure. If the location is a padded location in the virtual padded data structure, the virtual padding unit outputs a padding value rather than a value stored in the virtual padded data structure. If the location is a non-padded location in the virtual padded data structure, a value stored at the location is output.

    Cross-Component Optimizing Compiler Systems

    公开(公告)号:US20250004731A1

    公开(公告)日:2025-01-02

    申请号:US18214748

    申请日:2023-06-27

    Abstract: Cross-component optimizing compiler systems are described. In accordance with the described techniques, machine learning models receive components of source code to be compiled. The machine learning models generate component prediction functions for the components of the source code. A tuning engine selects parameters for the components of the source code based on the component prediction functions. Domain-specific language compilers compile the source code based on the selected parameters.

    Bank-Level Parallelism for Processing in Memory

    公开(公告)号:US20240103763A1

    公开(公告)日:2024-03-28

    申请号:US17953723

    申请日:2022-09-27

    CPC classification number: G06F3/0659 G06F3/0611 G06F3/0673

    Abstract: In accordance with the described techniques for bank-level parallelism for processing in memory, a plurality of commands are received for execution by a processing in memory component embedded in a memory. The memory includes a first bank and a second bank. The plurality of commands include a first stream of commands which cause the processing in memory component to perform operations that access the first bank and a second stream of commands which cause the processing in memory component to perform operations that access the second bank. A next row of the first bank that is to be accessed by the processing in memory component is identified. Further, a precharge command is scheduled to close a first row of the first bank and an activate command is scheduled to open the next row of the first bank in parallel with execution of the second stream of commands.

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