HARDWARE ACCELERATOR WITH ANALOG-CONTENT ADDRESSABLE MEMORY (A-CAM) FOR DECISION TREE COMPUTATION

    公开(公告)号:US20220122646A1

    公开(公告)日:2022-04-21

    申请号:US17071924

    申请日:2020-10-15

    Abstract: Examples described herein relate to a decision tree computation system in which a hardware accelerator for a decision tree is implemented in the form of an analog Content Addressable Memory (a-CAM) array. The hardware accelerator accesses a decision tree. The decision tree comprises of multiple paths and each path of the multiple paths includes a set of nodes. Each node of the decision tree is associated with a feature variable of multiple feature variables of the decision tree. The hardware accelerator combines multiple nodes among the set of nodes with a same feature variable into a combined single node. Wildcard values are replaced for feature variables not being evaluated in each path. Each combined single node associated with each feature variable is mapped to a corresponding column in the a-CAM array and the multiple paths of the decision tree to rows of the a-CAM array.

    Hardware accelerator with analog-content addressable memory (a-CAM) for decision tree computation

    公开(公告)号:US11615827B2

    公开(公告)日:2023-03-28

    申请号:US17071924

    申请日:2020-10-15

    Abstract: Examples described herein relate to a decision tree computation system in which a hardware accelerator for a decision tree is implemented in the form of an analog Content Addressable Memory (a-CAM) array. The hardware accelerator accesses a decision tree. The decision tree comprises of multiple paths and each path of the multiple paths includes a set of nodes. Each node of the decision tree is associated with a feature variable of multiple feature variables of the decision tree. The hardware accelerator combines multiple nodes among the set of nodes with a same feature variable into a combined single node. Wildcard values are replaced for feature variables not being evaluated in each path. Each combined single node associated with each feature variable is mapped to a corresponding column in the a-CAM array and the multiple paths of the decision tree to rows of the a-CAM array.

Patent Agency Ranking