SAP has been granted a patent for a method of graph processing in a scalable framework. The method involves partitioning a graph, distributing partitions to graph cores, executing algorithms, and exchanging vertex labels. The system includes data processors and memory storing instructions for these operations. GlobalData’s report on SAP gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on SAP, AI for workflow management was a key innovation area identified from patents. SAP's grant share as of February 2024 was 64%. Grant share is based on the ratio of number of grants to total number of patents.
Scalable graph processing framework using fpga with udfs
A recently granted patent (Publication Number: US11921786B2) discloses a system and method for graph processing using a distributed architecture. The system includes multiple graph cores that execute a graph processing algorithm by exchanging vertex labels via a crossbar interconnecting the cores. The method involves partitioning the graph into intervals and sub-intervals, with each core processing specific intervals and updating vertex labels based on received results from other cores. The system utilizes on-chip memory for non-sequential read requests during algorithm iterations, with each core coupled to a single memory channel for partition distribution.
Furthermore, the patent details the architecture of the crossbar, which includes bank shuffle and core shuffle levels for efficient routing of neighbor indices and vertex labels between graph cores. The graph cores can be implemented on a field programmable gate array (FPGA) and are synthesized based on user-defined functions for various graph processing algorithms like BFS, PR, WCC, and more. The method stored on a computer-readable medium outlines the steps for partitioning the graph, distributing partitions to cores, exchanging vertex labels, and determining the algorithm results based on received data from the cores. This innovative system and method provide a scalable and efficient solution for processing large graphs in parallel, enhancing performance and speed in graph analytics applications.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
