公开(公告)号：GB2599843A

公开(公告)日：2022-04-13

申请号：GB202200094

申请日：2020-06-11

Applicant: IBM

Inventor： LOKESH MOHAN GUPTA ,  KARL ALLEN NIELSEN ,  MATTHEW BORLICK ,  MICAH ROBISON

IPC: G06F3/06

Abstract: A method for dynamically altering a writes-per-day classification of multiple storage drives is disclosed. In one embodiment, such a method monitors, within a storage environment, an amount of overprovisioning utilized by multiple storage drives. Each storage drive has a writes-per-day classification associated therewith. Based on the amount of overprovisioning, the method periodically modifies the writes-per-day classification of the storage drives. The method then reorganizes the storage drives within various storage groups (e.g., RAID arrays, storage tiers, workloads, etc.) based on their writes-per-day classification. For example, the method may place, as much as possible, storage drives of the same writes-per-day classification within the same storage groups. A corresponding system and computer program product are also disclosed.

公开(公告)号：GB2580259B

公开(公告)日：2022-02-23

申请号：GB202004071

申请日：2018-08-20

Applicant: IBM

Inventor： LOKESH M GUPTA ,  MATTHEW BORLICK

IPC: G06F3/06 ,  G06F12/08 ,  H04L67/1097

Abstract: A computer-implemented method for thin provisioning using cloud based ranks comprises determining a total amount of unused physical storage space for all of a plurality of local ranks associated with a storage controller; comparing the total amount of unused physical storage space to a first threshold; in response to determining that the total amount of unused physical storage space is less than the first threshold, creating one or more cloud based ranks. Creating each of the one or more cloud based ranks comprises allocating storage space on one or more corresponding cloud storage devices via a cloud interface; mapping the allocated storage space to corresponding virtual local addresses; and grouping the virtual local addresses as a virtual local rank associated with the storage controller.

公开(公告)号：GB2607478A

公开(公告)日：2022-12-07

申请号：GB202211240

申请日：2020-12-15

Applicant: IBM

Inventor： BETH ANN PETERSON ,  LOKESH MOHAN GUPTA ,  MATTHEW RICHARD CRAIG ,  MATTHEW BORLICK

IPC: G06F12/0897

Abstract: Provided are computer program product, system, and method for managing data structures in a plurality of memory devices that are indicated to demote after initialization of the data structures. Indication is made to data structures to demote after initialization from a first level memory device to a second level memory device. The first level memory device has lower latency than the second level memory device. In response to completing initialization of the data structures in the first level memory device, copying the data structures indicated to demote after initialization from the first level memory device to the second level memory device and removing the data structures indicate to move after initialization from the first level memory device.

公开(公告)号：GB2588037B

公开(公告)日：2022-05-11

申请号：GB202019055

申请日：2019-05-13

Applicant: IBM

Inventor： LOKESH MOHAN GUPTA ,  MATTHEW BORLICK ,  KYLER ANDERSON ,  KEVIN JOHN ASH

IPC: G06N3/04 ,  G06F12/00 ,  G06N3/08

Abstract: Provided are a computer program product, system, and method for using a machine learning module to select one of multiple cache eviction algorithms to use to evict a track from the cache. A first cache eviction algorithm determines tracks to evict from the cache. A second cache eviction algorithm determines tracks to evict from the cache, wherein the first and second cache eviction algorithms use different eviction schemes. At least one machine learning module is executed to produce output indicating one of the first cache eviction algorithm and the second cache eviction algorithm to use to select a track to evict from the cache. A track is evicted that is selected by one of the first and second cache eviction algorithms indicated in the output from the at least one machine learning module.

公开(公告)号：GB2600042A

公开(公告)日：2022-04-20

申请号：GB202200098

申请日：2020-06-11

Applicant: IBM

Inventor： LOKESH MOHAN GUPTA ,  KARL ALLEN NIELSEN ,  MATTHEW BORLICK ,  MICAH ROBISON

IPC: G06F12/02

Abstract: A method for dynamically altering logical storage capacity within multiple storage drives is disclosed. In one embodiment, such a method monitors, within a storage environment, characteristics (e.g., age, wear, etc.) of multiple storage drives. Each storage drive has an amount of overprovisioning associated therewith. Based on the characteristics, the method periodically modifies a logical storage capacity of the storage drives in order to alter the amount of overprovisioning. The method then reorganizes the storage drives within various storage groups (e.g., RAID arrays, storage tiers, workloads, etc.) based on their logical storage capacity. For example, the method may place, as much as possible, storage drives of the same logical storage capacity within the same storage groups. A corresponding system and computer program product are also disclosed.

公开(公告)号：GB2588037A

公开(公告)日：2021-04-14

申请号：GB202019055

申请日：2019-05-13

Applicant: IBM

Inventor： LOKESH GUPTA ,  MATTHEW BORLICK ,  KYLER ANDERSON ,  KEVIN JOHN ASH

IPC: G06F12/00

Abstract: A machine learning module selects one of multiple cache eviction algorithms to use to evict a track from the cache. A first cache eviction algorithm determines tracks to evict from the cache. A second cache eviction algorithm determines tracks to evict from the cache, wherein the first and second cache eviction algorithms use different eviction schemes. At least one machine learning module is executed to produce output indicating one of the first cache eviction algorithm and the second cache eviction algorithm to use to select a track to evict from the cache. A track is evicted that is selected by one of the first and second cache eviction algorithms indicated in the output from the at least one machine learning module.

公开(公告)号：GB2585320A

公开(公告)日：2021-01-06

申请号：GB202017405

申请日：2019-04-01

Applicant: IBM

Inventor： LOKESH GUPTA ,  MATTHEW BORLICK ,  KEVIN JOHN ASH

IPC: G06F12/0866 ,  G06F3/06 ,  G06F12/0895

Abstract: Provided are a computer program product, system, and method for using track locks and stride group locks to manage cache operations. A group of tracks from the storage devices are stored in a cache. Exclusive track locks for tracks in the group in the cache are granted for writes to the tracks in the group in the cache, wherein exclusive track locks can be simultaneously held for writes to different tracks in the cache. An exclusive group lock for the group of tracks in the cache is granted to destage the tracks in the group from the cache to the storage devices. The exclusive group lock is released in response to completing the destage of the tracks in the group in the cache to the storage devices.

公开(公告)号：GB2607478B

公开(公告)日：2024-12-11

申请号：GB202211240

申请日：2020-12-15

Applicant: IBM

Inventor： BETH ANN PETERSON ,  LOKESH MOHAN GUPTA ,  MATTHEW RICHARD CRAIG ,  MATTHEW BORLICK

IPC: G06F12/0897 ,  G06F3/06

Abstract: Provided are computer program product, system, and method for managing data structures in a plurality of memory devices that are indicated to demote after initialization of the data structures. Indication is made to data structures to demote after initialization from a first level memory device to a second level memory device. The first level memory device has lower latency than the second level memory device. In response to completing initialization of the data structures in the first level memory device, the data structures indicated to demote after initialization are copied from the first level memory device to the second level memory device and removing the data structures indicate to move after initialization from the first level memory device.

公开(公告)号：GB2591424B

公开(公告)日：2021-11-10

申请号：GB202106810

申请日：2019-09-30

Applicant: IBM

Inventor： LOKESH GUPTA ,  KYLER ANDERSON ,  KEVIN JOHN ASH ,  MATTHEW BORLICK

IPC: G06N3/08 ,  G06F12/08

Abstract: A machine learning module receives inputs comprising attributes of a storage controller, where the attributes affect performance parameters for performing stages and destages in the storage controller. In response to an event, the machine learning module generates, via forward propagation, an output value that indicates whether to fill holes in a track of a cache by staging data to the cache prior to destage of the track. A margin of error is calculated based on comparing the generated output value to an expected output value, where the expected output value is generated from an indication of whether it is correct to fill holes in a track of the cache by staging data to the cache prior to destage of the track. An adjustment is made of weights of links that interconnect nodes of the plurality of layers via back propagation to reduce the margin of error.

公开(公告)号：GB2587314B

公开(公告)日：2021-09-15

申请号：GB202100441

申请日：2019-06-20

Applicant: IBM

Inventor： MATTHEW BORLICK ,  KARL ALLEN NIELSEN ,  CLINT HARDY ,  LOKESH GUPTA

IPC: G06F11/07 ,  G06F11/10 ,  G06N3/08 ,  G06N5/00 ,  G06N5/02 ,  G06N20/10

Abstract: Provided are a computer program product, system, and method for using a machine learning module to determine when to perform error checking of a storage unit. Input on attributes of at least one storage device comprising the storage unit are provided to a machine learning module to produce an output value. An error check frequency is determined from the output value. A determination is made as to whether the error check frequency indicates to perform an error checking operation with respect to the storage unit. The error checking operation is performed in response to determining that the error checking frequency indicates to perform the error checking operation.