International Business Machines Corporation

International Business Corporation

Beth Ann Peterson

Lokesh M Gupta

Kevin J Ash

Juan A Coronado

Matthew J Kalos

Kyler A Anderson

Matthew G Borlick

Susan Kay Candelaria

Brian Dow Clark

Harry M Yudenfriend

Theresa Mary Brown

Clint Alan Hardy

Warren Keith Stanley

Nedlaya Yazzie Francisco

Matthew Richard Craig

Suguang Li

David Michael Shackelford

John Richard Paveza

Roger Gregory Hathorn

Lisa R Martinez

Dale Francis Riedy, Jr

Chung Man Fung

John Glenn Thompson

Lisa Joan Gundy

Alfred Emilio Sanchez

Jennifer Shinobu Shioya

Nicolas Marc Clayton

Jeffrey Allen Berger

Ronald E Bretschneider

Scott Brady Compton

Kenneth Wayne Todd

Deborah A Furman

Ilene A Goldman

Christina Ann Lara

Yong Guo

Christopher Daniel Filachek

Jie Tian

Max D Smith

Karl Allen Nielsen

Peter Grimm Sutton

Gail Andrea Spear

Richard Anthony Ripberger

Brian Anthony Rinaldi

Micah Robison

Raul Eduardo Saba

Olympia Gluck

Jared Michael Minch

Edward Hsiu-Wei Lin

Helena Cornelia Burton

Mark A Lehrer

Samantha A Utter

Xavier Edgar Somoza

Paulina Acevedo

Veronica A Reeves-Voeltner

Michael T Benhase

Matthew John Ward

John Charles Elliott

Todd Charles Sorenson

Patricia G Driever

Joseph S Hyde, Ii

Thomas Charles Jarvis

Kurt Allen Lovrien

Edward Lin

Louis Alonso Rasor

James E Olson

Wayne Erwin Rhoten

Brian Sean McCain

Qiang Xie

Brian S Lee

Dinh Hai Le

Ashwani Kumar

Veronica S Davila

Aaron Eugene Taylor

Clarisa Valencia

Phu Nguyen

Jayson Elliott Tsingine

Donald Prentiss Terry

James Lamar Hood

James D Marwood, Jr

Justin David Suess

Roman Yusufov

Jack Neil Licano, Jr

Russell Bernard Krueger

Paul W Garcia

Provided are a computer program product, system, and method for determining to migrate data between compressed storage devices and non-compressed storage devices in a storage system. The storage system provides compressed storage devices having native data compression and a non-compressed storage devices not configured to have native compression. A determination is made of storage usage factors for the compressed storage devices and the non-compressed storage devices. A determination is made whether to move data between the compressed storage devices and the non-compressed storage devices based on the storage usage factors. Data is moved between the compressed storage devices and the non-compressed storage devices in response to determining to move the data between the compressed storage devices and the non-compressed storage devices.

Determining to migrate data between compressed storage devices and non-compressed storage devices in a storage system

Described are techniques for selecting compressed or non-compressed data storage using hints for a dataset. The techniques include receiving a dataset at a data storage system that manages storage location on compressed data storage and non-compressed data storage. The techniques further include determining, by the data storage system, that the dataset includes one or more hints for selecting a storage location for the dataset from one of the storage locations managed by the data storage system. The techniques further include selecting, by the data storage system, the storage location for the dataset based in part on the one or more hints and storing the dataset to the storage location.

Hinting information for selecting a storage location for a dataset

Provided are a computer program product, system, and method for determining a storage device type on which to store extents of data in a storage system. The storage system provides a first storage device type that has native data compression at a first compression ratio and a second storage device type that has native data compression at a second compression ratio. The second compression ratio is higher than the first compression ratio. A determination is made for an extent to store the extent on the first storage device type or the second storage device type based on access frequency to data in the extent and an Input/Output (I/O) priority level for the extent. The extent is stored on the determined first or second storage device type.

Determining a storage device type on which to store extents of data in a storage system

Provided are a storage device, system, and method for performance enhancing measures for storage in which high-performance volumes reside. Indication is made of a volume configured in the arrays to have high-performance. An array is determined storing the indicated volume. A determination is made of storage devices in which the determined array resides. The storage devices are enabled to perform garbage collection on blocks of data having valid and invalid pages in the storage devices at a first garbage collection rate and a second garbage collection rate. The second garbage collection rate causes a storage device to perform garbage collection with respect to a greater number of blocks than the first garbage collection rate. A command is sent to the determined storage devices to garbage collect at the second garbage collection rate.

Garbage collection for storage in which high-performance volumes reside

Provided are a computer program product, system, and method for generating data protection directives to provide to a storage controller to control access to data in cache. A data protection directive is generated for a data subset indicating access request type and a protective action with respect to the access request type for the data subset. The data protection directive is transmitted to the storage controller. The storage controller includes the data protection directive in metadata for the data subset. The data protection directive causes the storage controller to perform the protective action in response to an access request of the access request type to a portion of the data subset.

Generating data protection directives to provide to a storage controller to control access to data in cache

A computer-implemented method, according to one approach, includes: monitoring performance in NVRAM having a plurality of memory blocks. Moreover, a change in the flow rate of I/O requests received at the NVRAM is identified as a result of the monitoring. In response to identifying the change is an increase in the flow rate of received I/O requests, the percentage of invalid pages in a given block of NVRAM that triggers garbage collection to be performed on the given block is increased. However, in response to identifying the change is a decrease in the flow rate of received I/O requests, the percentage of invalid pages in a given block that triggers garbage collection to be performed on the given block is decreased.

Adjusting garbage collection based on input/output flow rates

Provided are a computer program product, system, and method for determining whether to compress data at a source device to transmit to a target device. A determination is made of network bandwidth between the source device and the target device. The source device transmits data to the target device. A determination is made of source available processor resources on the source device and target available processor resources on the target device. A determination is made as to whether to compress data at the source device to transmit to the target device based on the network bandwidth, the source available processor resources, and the target available processor resources. Compression is initiated, on the source device, of the data to transmit to the target device in response to determining that the source device is to compress the data.

Determining whether to compress data at a source device to transmit to a target device

Provided are techniques for task adjustment for uniform performance of drives. Arrays are created for different drive types. Performance benchmarks are run for each of the arrays to compute a stage maximum value and a destage maximum value for each of the drive types. At run time, in response to determining that a mode indictor indicates a uniform performance mode, a maximum number of stage Task Control Blocks (TCBs) are set to a stage maximum uniform value and a maximum number of destage TCBs are set to a destage maximum uniform value. The stage of first data is performed using an actual number of stage TCBs that do not exceed the maximum number of stage TCBs. The destage of second data is performed using an actual number of destage TCBs that do not exceed the maximum number of destage TCBs.

Task adjustment for uniform performance of drives

Provided are a computer program product, system, and method for using a transient cache list and prolonged cache list to manage tracks in cache based on a demotion hint with a track access request. A track is staged into the cache in response to a request for the track. A determination is made as to whether the request provides a demotion hint. The track is indicated in a transient cache list in response to determining that the request provides the demotion hint. The track is indicated in a prolonged cache list in response to determining that the request does not provide the demotion hint. The track is demoted from the cache in response to the request for the track comprising a read request, returning the track to the read request, and the track is indicated in the transient cache list.

Using a transient cache list and prolonged cache list to manage tracks in cache based on a demotion hint with a track access request

Provided are a computer program product, system, and method for determining whether to process a host request by training a machine learning module. A machine learning module receives input information related to at least one of running tasks, mail queue messages related to host request processing, I/O request processing, and a host request received from a host system and produces output for the host request indicating whether to process the host request. A determination is made of output produced from the machine learning module based on the input information for a received host request. A determination is made of an expected output based on a measured system resource usage and an optimum system resource usage. The machine learning module is retrained with the input information, the output produced from the machine learning module, and the expected output and provided to determine whether to process a received host request.

Determining whether to process a host request by training a machine learning module

Provided are a computer program product, system, and method for managing swappable data structures in a plurality of memory devices based on access counts of the data structures. Data structures indicated as swappable are updated less frequently than most frequently updated data structures. Data structures not indicated as swappable are maintained in a first level memory device and not moved to a second level memory device. The first level memory device has lower latency than the second level memory device. Access counts are maintained for the data structures stored in the first level memory device that are indicated as swappable. Data structures are selected in the first level memory device having lowest access counts. The selected data structures are removed from the first level memory device and retained in the second level memory device.

Managing swappable data structures in a plurality of memory devices based on access counts of the data structures

Provided are a computer program product for managing tracks in a storage in a cache. An active track data structure indicates tracks in the cache that have an active status. An active bit in a cache control block for a track is set to indicate active for the track indicated as active in the active track data structure. In response to processing the cache control block, a determination is made, from the cache control block for the track, whether the track is active or inactive to determine processing for the cache control block.

Maintaining an active track data structure to determine active tracks in cache to process

A computer-implemented method, according to one embodiment, includes: in response to a determination that an available capacity of one or more buffers in a primary cache is not outside a predetermined range, using the one or more buffers in the primary cache to satisfy all incoming I/O requests. In response to a determination that the available capacity of the one or more buffers in the primary cache is outside the predetermined range, one or more buffers in a secondary cache are allocated, and the one or more buffers in the secondary cache are used to satisfy at least some of the incoming I/O requests.

Using multi-tiered cache to satisfy input/output requests

Provided are a computer program product, system, and method for using track status information on active or inactive status of track to determine whether to process a host request on a fast access channel. A host request to access a target track is received on a first channel to the host. A determination is made as to whether the target track has active or inactive status. The target track has active status when at least one process currently maintains a lock on the target track that prevents access and the target track has inactive status when no process maintains a lock on the target track that prevents access. Fail is returned to the host to cause the host to resend the host request on a second channel in response to the target track having the active status. The first channel has lower latency than the second channel.

Using track status information on active or inactive status of track to determine whether to process a host request on a fast access channel

Provided are a computer program product, system, and method for determining status of tracks in storage cached in a cache for a host. A storage controller receives from the host a list of tracks for the host to access and determines whether the tracks in the list are available in the cache for immediate access. A response is returned to the host indicating the tracks as one of available in the cache for immediate access and not available in the cache for immediate access.

Providing availability status on tracks for a host to access from a storage controller cache

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Tucson, AZ, United States of America

Beth Ann Peterson