中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

19 records (took 0.017 seconds)

    ADDRESS TRANSLATION AND DATA PRE-FETCH IN A CACHE MEMORY SYSTEM
    13.
    发明申请
    ADDRESS TRANSLATION AND DATA PRE-FETCH IN A CACHE MEMORY SYSTEM 审中-公开
    地址转换和数据缓存在缓存存储器系统中

    公开(公告)号：US20170024145A1

    公开(公告)日：2017-01-26

    申请号：US14807754

    申请日：2015-07-23

    Applicant: QUALCOMM INCORPORATED

    Inventor： TAREK ZGHAL ,  Alain Dominique Artieri ,  Jason Edward Podaima ,  Meghal Varia ,  Serag GadelRab

    IPC: G06F3/06 ,  G06F12/08

    CPC classification number: G06F3/0611 ,  G06F3/0656 ,  G06F3/0673 ,  G06F12/0862 ,  G06F2212/1021 ,  G06F2212/602 ,  G06F2212/6026 ,  G06F2212/6028 ,  G06F2212/654

    Abstract: Systems, methods, and computer program products are disclosed for reducing latency in a system that includes one or more processing devices, a system memory, and a cache memory. A pre-fetch command that identifies requested data is received from a requestor device. The requested data is pre-fetched from the system memory into the cache memory in response to the pre-fetch command. The data pre-fetch may be preceded by a pre-fetch of an address translation. A data access request corresponding to the pre-fetch command is then received, and in response to the data access request the data is provided from the cache memory to the requestor device.

    Abstract translation: 公开了系统，方法和计算机程序产品，用于减少包括一个或多个处理设备，系统存储器和高速缓冲存储器的系统中的延迟。 从请求器设备接收到识别所请求数据的预取命令。 响应于预取命令，将所请求的数据从系统存储器预取入高速缓冲存储器。 之前的数据预取可以预先获取地址转换。 然后接收与预取命令相对应的数据访问请求，并且响应于数据访问请求，将数据从高速缓冲存储器提供给请求器设备。

    Concurrent optimization of machine learning model performance
    14.
    发明授权
    Concurrent optimization of machine learning model performance 有权

    公开(公告)号：US11907810B2

    公开(公告)日：2024-02-20

    申请号：US16515711

    申请日：2019-07-18

    Applicant: QUALCOMM Incorporated

    Inventor： Serag Gadelrab ,  James Esliger ,  Meghal Varia ,  Kyle Ernewein ,  Alwyn Dos Remedios ,  George Lee

    IPC: G06N20/00 ,  G06F11/34 ,  G06N5/04

    CPC classification number: G06N20/00 ,  G06F11/3466 ,  G06N5/04

    Abstract: Certain aspects of the present disclosure provide techniques for concurrently performing inferences using a machine learning model and optimizing parameters used in executing the machine learning model. An example method generally includes receiving a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. At least a first inference is performed on the data set using the machine learning model to meet a latency specified for generation of the first inference from receipt of the request. While performing the at least the first inference, operational parameters resulting in inference performance approaching the performance metric targets are identified based on the machine learning model and operational properties of the computing device. The identified operational parameters are applied to performance of subsequent inferences using the machine learning model.

    System and method for dynamic control of shared memory management resources
    18.
    发明授权
    System and method for dynamic control of shared memory management resources 有权

    公开(公告)号：US10067691B1

    公开(公告)日：2018-09-04

    申请号：US15448095

    申请日：2017-03-02

    Applicant: QUALCOMM INCORPORATED

    Inventor： Serag Gadelrab ,  Jason Edward Podaima ,  Kyle Ernewein ,  Meghal Varia

    IPC: G06F3/06 ,  G06F9/50 ,  G06F12/10 ,  G06F12/1009

    Abstract: A method and system for dynamic control of shared memory resources within a portable computing device (“PCD”) are disclosed. A limit request of an unacceptable deadline miss (“UDM”) engine of the portable computing device may be determined with a limit request sensor within the UDM element. Next, a memory management unit modifies a shared memory resource arbitration policy in view of the limit request. By modifying the shared memory resource arbitration policy, the memory management unit may smartly allocate resources to service translation requests separately queued based on having emanated from either a flooding engine or a non-flooding engine.

Patent Agency Ranking