Dynamic modification of coherent atomic memory operations

    公开(公告)号:US11604737B1

    公开(公告)日:2023-03-14

    申请号:US17516860

    申请日:2021-11-02

    Abstract: A processing device determines a scope indicating at least a portion of the processing system and target data from atomic memory operation to be performed. Based on the scope, the processing device determines one or more hardware parameters for at least a portion of the processing system. The processing device then compares the hardware parameters to the scope and target data to determine one or more corrections. The processing device then provides the scope, target data, hardware parameters, and corrections to a plurality of hardware lookup tables. The hardware lookup tables are configured to receive the scope, target data, hardware parameters, and corrections as inputs and output values indicating one or more coherency actions and one or more orderings. The processing device then executes one or more of the indicated coherency actions and the atomic memory operation based on the indicated ordering.

    Dual Purpose Millimeter Wave Frequency Band Transmitter

    公开(公告)号:US20230061698A1

    公开(公告)日:2023-03-02

    申请号:US18048689

    申请日:2022-10-21

    Abstract: Systems, apparatuses, and methods for implementing a dual-purpose millimeter-wave frequency band transmitter are disclosed. A system includes a dual-purpose transmitter sending a video stream over a wireless link to a receiver. In some embodiments, the video stream is generated as part of an augmented reality (AR) or virtual reality (VR) application. The transmitter operates in a first mode to scan and map an environment of the transmitter and receiver. The transmitter generates radio frequency (RF) signals in a first frequency range while operating in the first mode. Additionally, the transmitter operates in a second mode to send video data to the receiver, and the transmitter generates RF signals in the first frequency range while operating in the second mode.

    Flexible dictionary sharing for compressed caches

    公开(公告)号:US11586555B2

    公开(公告)日:2023-02-21

    申请号:US17231957

    申请日:2021-04-15

    Abstract: Systems, apparatuses, and methods for implementing flexible dictionary sharing techniques for caches are disclosed. A set-associative cache includes a dictionary for each data array set. When a cache line is to be allocated in the cache, a cache controller determines to which set a base index of the cache line address maps. Then, a selector unit determines which dictionary of a group of dictionaries stored by those sets neighboring this set would achieve the most compression for the cache line. This dictionary is then selected to compress the cache line. An offset is added to the base index of the cache line to generate a full index in order to map the cache line to the set corresponding to this chosen dictionary. The compressed cache line is stored in this set with the chosen dictionary, and the offset is stored in the corresponding tag array entry.

    NOISE MITIGATION IN SINGLE ENDED LINKS

    公开(公告)号:US20230046477A1

    公开(公告)日:2023-02-16

    申请号:US17545108

    申请日:2021-12-08

    Abstract: A data transmission system includes a first circuit, a second circuit, and a reference voltage generation circuit. The first circuit includes a transmitter powered by a first power supply voltage and having an input for receiving a data output signal, and an output. The second circuit includes a receiver powered by a second power supply voltage and having a first input coupled to the output of the transmitter, a second input for receiving a reference voltage, and an output for providing a data input signal. The reference voltage generation circuit forms the reference voltage by mixing a first signal generated by the first circuit based on the first power supply voltage and a second signal generated by the second circuit based on the second power supply voltage.

    Fused convolution and batch normalization for neural networks

    公开(公告)号:US11573765B2

    公开(公告)日:2023-02-07

    申请号:US16219154

    申请日:2018-12-13

    Abstract: A processing unit implements a convolutional neural network (CNN) by fusing at least a portion of a convolution phase of the CNN with at least a portion of a batch normalization phase. The processing unit convolves two input matrices representing inputs and weights of a portion of the CNN to generate an output matrix. The processing unit performs the convolution via a series of multiplication operations, with each multiplication operation generating a corresponding submatrix (or “tile”) of the output matrix at an output register of the processing unit. While an output submatrix is stored at the output register, the processing unit performs a reduction phase and an update phase of the batch normalization phase for the CNN. The processing unit thus fuses at least a portion of the batch normalization phase of the CNN with a portion of the convolution.

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