International Business Machines Corporation

Globalfoundries Inc.

International Business Corporation

Machines Corporation

Kevin J Ash

Lokesh M Gupta

Kyler A Anderson

Matthew G Borlick

Matthew J Kalos

Michael T Benhase

Beth Ann Peterson

Kenneth Wayne Todd

Trung Ngoc Nguyen

Brian Anthony Rinaldi

Karl Allen Nielsen

Clint Alan Hardy

David Blair Whitworth

Matthew Richard Craig

Alfred Emilio Sanchez

David Frank Mannenbach

Gail Andrea Spear

Micah Robison

Steven Robert Lowe

John Charles Elliott

Susan Kay Candelaria

Yu-Cheng Hsu

Louis Alonso Rasor

Jared Michael Minch

Carol Santich Mellgren

Warren Keith Stanley

Joseph S Hyde, Ii

Chung Man Fung

Will A Wright

Benjamin Jay Donie

Andreas Bernardus Mattias Koster

Evangelos Stavros Eleftheriou

Roger Gregory Hathorn

Roman Alexander Pletka

Brent Cameron Beardsley

Richard Anthony Ripberger

Robert Akira Kubo

Robert Haas

Theodore Timothy Harris, Jr

Thomas Charles Jarvis

Edward Lin

Suguang Li

David Brent Schreiber

Boyan Zhao

Keneth W Todd

William Frank Micka

Todd Charles Sorenson

Ioannis Koltsidas

Shachar Fienblit

Steven Edward Klein

Brian James Cagno

Stephen LaRoux Blinick

Sonny Earl Williams

Xiao-Yu Hu

Vernon John Legvold

Juan Antonio Yanes

Seamus Burke

Xiaoyu Hu

Jack Harvey Derenburger

William Dennis Williams

Raymond L Parsons

Maoyun Tang

Tim Stephen Vande Zande

Samantha A Utter

Jeffrey Michael Barnes

Joseph Dean Ohrazda

Richard H Grossman

Pablo A Rodriguez

Rose L Manz

Kyle A Anderson

Provided are a computer program product, system, and method for indicating extents of tracks in mirroring queues based on information gathered on tracks in extents in cache. Extent information on an extent of tracks in a cache indicated in an active cache list is processed in response to destaging a track from the active cache list to add to a demote list used to determine tracks to remove from the cache. The extent information is related to a number of modified tracks in an extent destaged from the active cache list. The extent information for the extent is used to determine one of a plurality of mirroring queues to indicate the extent including modified tracks. A mirroring queue having a higher priority than another mirroring queue is processed at a higher rate to determine extents of tracks to mirror from the cache to the secondary storage.

Indicating extents of tracks in mirroring queues based on information gathered on tracks in extents in cache

Provided are a computer program product, system, and method for saving track metadata format information for tracks demoted from cache for use when the demoted track is later staged into cache. A track is demoted from the cache and indicated in a demoted track list. The track format information for the demoted track is saved, wherein the track format information indicates a layout of data in the track. The saved track format information for the demoted track is used when the demoted track is staged back into the cache.

Saving track metadata format information for tracks demoted from cache for use when the demoted track is later staged into cache

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 using trap cache segments to detect malicious processes. A trap cache segment to the cache for data in the storage and indicated as a trap cache segment. Cache segments are added to the cache having data from the storage that are not indicated as trap cache segments. A memory function call from a process executing in the computer system reads data from a region of a memory device to output the read data to a buffer of the memory device. A determination is made as to whether the region of the memory device includes the trap cache segment. The memory function call is blocked and the process is treated as a potentially malicious process in response to determining that the region includes the trap cache segment.

Using trap cache segments to detect malicious processes

Provided are a computer program product, system, and method for determining tracks to prestage into cache from a storage. Information is provided related to determining tracks to prestage from the storage to the cache in a stage group of sequential tracks including a trigger track comprising a track number in the stage group at which to start prestaging tracks and Input/Output (I/O) activity information to a machine learning module. A new trigger track in the stage group at which to start prestaging tracks is received from the machine learning module having processed the provided information. The trigger track is set to the new trigger track. Tracks are prestaged in response to processing an access request to the trigger track in the stage group.

Dynamically determining tracks to prestage from storage to cache using a machine learning module

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 I/O request type specific cache directories in accordance with the present description. In one embodiment, by limiting track entries of a cache directory to a specific I/O request type, the size of the cache directory may be reduced as compared to general cache directories for I/O requests of all types, for example. As a result, look-up operations directed to such smaller size I/O request type specific cache directories may be completed in each directory more quickly. In addition, look-ups may frequently be successfully completed after a look-up of a single I/O request type specific cache directory, improving the speed of cache look-ups and providing a significant improvement in system performance. Other aspects and advantages are provided, depending upon the particular application.

I/O request type specific cache directories

Provided are a computer program product, system, and method for using a track format code in a cache control block for a track in a cache to process read and write requests to the track in the cache. A track format table associates track format codes with track format metadata. A determination is made as to whether the track format table has track format metadata matching track format metadata of a track staged into the cache. A determination is made as to whether a track format code from the track format table for the track format metadata in the track format table matches the track format metadata of the track staged. A cache control block for the track being added to the cache is generated including the determined track format code when the track format table has the matching track format metadata.

Using a track format code in a cache control block for a track in a cache to process read and write requests to the track in the cache

A method for improving cache hit ratios for selected storage elements within a storage system includes storing, in a cache of a storage system, non-favored storage elements and favored storage elements. The favored storage elements are retained in the cache longer than the non-favored storage elements. The method maintains a first LRU list containing entries associated with non-favored storage elements and designating an order in which the non-favored storage elements are evicted from the cache, and a second LRU list containing entries associated with favored storage elements and designating an order in which the favored storage elements are evicted from the cache. The method periodically scans the first LRU list for non-favored storage elements that have changed to favored storage elements, and the second LRU list for favored storage elements that have changed to non-favored storage elements. A corresponding system and computer program product are also disclosed.

LRU list reorganization for favored and unfavored volumes

Using a machine learning module to dynamically determine tracks to prestage from storage to cache

A method to prevent starvation of non-favored volumes in cache is disclosed. In one embodiment, such a method includes storing, in a cache of a storage system, non-favored storage elements and favored storage elements. A cache demotion algorithm is used to retain the favored storage elements in the cache longer than the non-favored storage elements. The method designates a maximum amount of storage space that the favored storage elements are permitted to consume in the cache. In preparation to free storage space in the cache, the method determines whether an amount of storage space consumed by the favored storage elements in the cache has reached the maximum amount. If so, the method frees storage space in the cache by demoting favored storage elements. If not, the method frees storage space in the cache in accordance with the cache demotion algorithm. A corresponding system and computer program product are also disclosed.

Non-favored volume cache starvation prevention

In one embodiment, storage drive dependent track removal processing logic performs destage tasks for tracks cached in a cache as a function of whether the storage drive is classified as a fast class or as slow class of storage drives, for example. In one embodiment, a destage task configured for a slow class storage drive, transfers an entry for a track selected for destaging from a main cache list to a wait cache list to await destaging to the slow class drive. A destage task configured for a fast class storage drive allows the cache list entry for the selected track to remain on the main cache list while the selected track is being destaged to the fast class storage drive, thereby bypassing the transfer of the entry to a wait cache list. Other features and aspects may be realized, depending upon the particular application.

Storage drive dependent track removal in a cache for storage

A method for maintaining statistics for data elements in a cache is disclosed. The method maintains a heterogeneous cache comprising a higher performance portion and a lower performance portion. The method maintains, within the lower performance portion, a ghost cache containing statistics for data elements that are currently contained in the heterogeneous cache, and data elements that have been demoted from the heterogeneous cache within a specified time interval. The method calculates a size of the ghost cache based on an amount of frequently accessed data that is stored in backend storage volumes behind the heterogeneous cache. The method alters the size of the ghost cache as the amount of frequently accessed data changes. A corresponding system and computer program product are also disclosed.

Calculating and adjusting ghost cache size based on data access frequency

Growing community of inventors

Tucson, AZ, United States of America

Kevin J Ash