2 results about "Multicore cpu" patented technology

A hardware accelerated solution of the SPM (Sequential Pattern Mining) is proposed using Micron's Automata Processor (AP), a hardware implementation of non-deterministic finite automata (NFAs) The Generalized Sequential Pattern (GSP) algorithm for SPM searching exposes massive parallelism, and is therefore well-suited for AP acceleration. The multi puss pruning strategy of the GSP is implemented is the APs fast reconfigurability. A generalized automaton structure is proposed by flattening sequential patterns to simple strings to reduce compilation time and to minimize overhead of reconfiguration. Up to 90× and 29× speedups are achieved by the AP-accelerated GSP on six real-world datasets, when compared with the optimized multicore CPU (Central Processing Unit) and GPU (Graphics Processing Unit) GSP implementations, respectively. The proposed CPU-AP solution also outperforms the state-of-the-art PrefixSpan and SPADE (Sequential PAttern Discovery using Equivalence classes algorithms on multicore CPU by up to 452× and 49× speedups.

The present application relates to a kind of intelligent inference framework optimization method based on real-time operating system and multicore CPU, belong to real-time operating system field.The method of the present application includes: task splitting and core allocation: inference task is divided according to the way of tile, each core is responsible for processing the inference task of a tile;Each tile will be allocated to idle core and be processed in parallel;Real-time monitoring and dynamic adjustment: system will monitor the load condition of each core in real time, and dynamically adjust the allocation of task according to the idleness of core and the complexity of task;Through work stealing technique, if the load of a core is low, it will obtain task from other core to balance the load;Priority and task scheduling: when processing the task with higher real-time requirement, it is preferentially allocated to high-priority core.The present application effectively improves the inference efficiency and resource utilization of system.