公开(公告)号：US20230035666A1

公开(公告)日：2023-02-02

申请号：US17391463

申请日：2021-08-02

Applicant: Seagate Technology LLC

Inventor： Anatolii Bilenko ,  Yuriy V. Umanets ,  Maksym Medvied

IPC: G06F11/30 ,  G06F11/34 ,  G06F11/32 ,  G06N3/08

Abstract: A method of preparing an input vector for a neural network includes capturing a plurality of information about a storage system, including workload types, a processing graph, and read/write histograms, and creating a correlation matrix from processing times of different levels of processes in a workload of the storage system. The input vector is prepared with a workload vector representing the workload types, a behavior matrix representing the processing graph, a read/write histogram shape matrix representing the read/write histograms, and the correlation matrix.

公开(公告)号：US20230205667A1

公开(公告)日：2023-06-29

申请号：US17705207

申请日：2022-03-25

Applicant: Seagate Technology LLC

Inventor： Anatolii Bilenko ,  Nikita Danilov ,  Maksym Medvied

IPC: G06F11/34 ,  G06F16/182

CPC classification number: G06F11/3495 ,  G06F11/3447 ,  G06F16/182

Abstract: Data access requests targeted to a distributed filesystem are tracked. The data access requests are distributed to different processes running on one more storage servers. For each of the processes, times of events within each of the processes is determined and the events are associated with an event identifier. Data may be stored that such as times of operations, event identifiers, and relationship data between the processes associated with the data access requests. The stored data characterizes different phases of the data access requests, which can be presented to a user for system analysis.