A non-volatile storage system that is implementing a storage region (e.g., a persistent memory region) which is accessible to a host (e.g., via a PCIe connection) and a cache for the storage region shares details of the structure of the storage region and/or the cache (e.g., cache segment size). With awareness of the shared details of the structure of the storage region and/or the cache, the host arranges and sends out requests to read data from the persistent memory region in a manner that takes advantage of parallelism within the non-volatile storage system. For example, the host may initially send out one read request per cache segment to cause the non-volatile storage system to load the cache. Subsequently, additional read requests are made to the non-volatile storage system, with the data already loaded (or starting to load) in the cache, thereby increasing performance.

Cache slots on a storage system may be shared between entities processing write operations for logical storage unit (LSU) tracks and entities performing remote replication for write operations for the LSU tracks. If a new write operation is received on a first storage system (S1) for a track of an LSU (R1) when the cache slot mapped to the R1 track is locked by a process currently transmitting data of the cache slot to a second storage system (S2), a new cache slot may be allocated to the R1 track, the data of the original cache slot copied to the new cache slot, and the new write operation for the R1 track initiated on S1 using the new cache slot; while the data of the original cache slot is independently, and perhaps concurrently, transmitted to S2 to be replicated in R2, the LSU on S2 that is paired with R1.

Operational information in a storage system is collected regarding storage media storage tiers, devices, drives, tracks on drives, and logical storage layers, to determine an estimated amount of time it will take to write data from cache to the intended drive when a new write operation arrives at the storage system. This information is then used to decide which type of cache is most optimal to store the data for the write operation, based on the estimated amount of time it will take to write data out from the cache. By allocating cache slots from a faster cache to write operations that are expected to quickly be written out to memory, and allocating cache slots from the slower cache to write operations that are expected to take more time to be written out to memory, it is possible to increase the availability of the cache slots in the faster cache.

A computational device receives indications of a minimum retention time and a maximum retention time in cache for a first plurality of tracks, wherein no indications of a minimum retention time or a maximum retention time in the cache are received for a second plurality of tracks. A cache management application demotes a track of the first plurality of tracks from the cache, in response to determining that the track is a least recently used (LRU) track in a LRU list of tracks in the cache and the track has been in the cache for a time that exceeds the minimum retention time. The cache management application demotes the track of the first plurality of tracks, in response to determining that the track has been in the cache for a time that exceeds the maximum retention time.

A computational device receives an indication of a minimum retention time in a cache for a plurality of tracks of an application. In response to determining that tracks of the application that are stored in the cache exceed a predetermined threshold in the cache, the computational device demotes one or more tracks of the application from the cache even though a minimum retention time in cache has been indicated for the one or more tracks of the application, while performing least recently used (LRU) based replacement of tracks in the cache.

Operational information in a storage system is collected regarding storage media storage tiers, devices, drives, tracks on drives, and logical storage layers, to determine an estimated amount of time it will take to write data from cache to the intended drive when a new write operation arrives at the storage system. This information is then used to decide which type of cache is most optimal to store the data for the write operation, based on the estimated amount of time it will take to write data out from the cache. By allocating cache slots from a faster cache to write operations that are expected to quickly be written out to memory, and allocating cache slots from the slower cache to write operations that are expected to take more time to be written out to memory, it is possible to increase the availability of the cache slots in the faster cache.

A deduplication engine maintains a hash table containing hash values of tracks of data stored on managed drives of a storage system. The deduplication engine keeps track of how frequently the tracks are accessed by the deduplication engine using an exponential moving average for each track. Target tracks which are frequently accessed by the deduplication engine are cached in local memory, so that required byte-by-byte comparisons between the target track and write data may be performed locally rather than requiring the target track to be read from managed drives. The deduplication engine implements a Least Recently Used (LRU) cache data structure in local memory to manage locally cached tracks of data. If a track is to be removed from local memory, a final validation of the target track is implemented on the version stored in managed resources before evicting the track from the LRU cache.

When a read request for the data portion is received from an application executing on a host, the host may determine whether the data portion is in host cache, and if so, whether the logical storage unit of the data portion is shared by another host system. If there is another host system sharing the logical storage unit, a latest version stored on the storage system may be determined and compared to the version stored in the host cache. If the version in the host cache is the same as the latest version stored on the storage system, the data portion may be retrieved from the host cache. If the version in the host cache is not the latest version stored on the storage system, the data portion may be retrieved from the storage system, and the host cache may be updated with the latest version of the data portion.

Provided are a computer program product, system, and method for determining sectors of a track to stage into cache using a machine learning module. Performance attributes of system components affected by staging tracks from the storage to the cache are provided to a machine learning module. An output is received, from the machine learning module having processed the provided performance attributes, indicating a staging strategy indicating sectors of a track to stage into the cache comprising one of a plurality of staging strategies. Sectors of an accessed track that is not in the cache are staged into the cache according to the staging strategy indicated in the output.

Provided are a computer program product, system, and method for using insertion points to determine locations in a cache list at which to indicate tracks in a shared cache accessed by a plurality of processors. A plurality of insertion points to a cache list for the shared cache having a least recently used (LRU) end and a most recently used (MRU) end identify tracks in the cache list. For each processor, of a plurality of processors, for which indication of tracks accessed by the processor is received, a determination is made of insertion points of the provided insertion points at which to indicate the tracks for which indication is received. The tracks are indicated at positions in the cache list with respect to the determined insertion points.