Abstract: A cache hit is generated, in response to receiving an input/output (I/O) command over a bus interface. An update for a metadata track is stored in a buffer associated with a central processing unit (CPU) that processes the I/O command, in response to generating the cache hit. The metadata track is asynchronously updated from the buffer with the stored update for the metadata track in the buffer.

Abstract: 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.

Abstract: A host computational device transmits a first write command with a first token over a first interface to a storage controller. In response to receiving an indication by the host computational device that the first write command has failed in the storage controller, the host computational device transmits a second write command with a second token over a second interface to the storage controller, wherein the second write command is a retry of the first write command that failed, wherein the second token is identical to the first token, and wherein the second interface is a slower communication link than the first interface.

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.

Abstract: 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.

Abstract: In response to an end of track access for a track in a cache, a determination is made as to whether the track has modified data and whether the track has one or more holes. In response to determining that the track has modified data and the track has one or more holes, an input on a plurality of attributes of a computing environment in which the track is processed is provided to a machine learning module to produce an output value. A determination is made as to whether the output value indicates whether one or more holes are to be filled in the track. In response to determining that the output value indicates that one or more holes are to be filled in the track, the track is staged to the cache from a storage drive.

Abstract: In response to determining, by a storage controller, that a first process is to perform a write operation, a customer data track in a cache is configured for exclusive access while waiting for the write operation on the customer data track to be performed by the first process. In response to configuring the customer data track for the exclusive access, a copy of a metadata track is generated, wherein the metadata track stores metadata information of the customer data track and is configured for shared access. The copy of the metadata track is configured to provide exclusive access to a second process to perform operations on the copy of the metadata track, wherein the first process is able to perform the write operation on the customer data track that causes the metadata track to be updated while the second process performs the operations on the copy of the metadata track.

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.

Abstract: Copy source to target operations may be selectively and preemptively undertaken in advance of source destage operations. In another aspect, logic detects sequential writes including large block writes to point-in-time copy sources. In response, destage tasks on the associated point-in-time copy targets are started which include in one embodiment, stride-aligned copy source to target operations which copy unmodified data from the point-in-time copy sources to the point-in-time copy targets in alignment with the strides of the target. As a result, when write data of write operations is destaged to the point-in-time copy sources, such source destages do not need to wait for copy source to target operations since they have already been performed. In addition, the copy source to target operations may be stride-aligned with respect to the stride boundaries of the point-in-time copy targets. Other features and aspects may be realized, depending upon the particular application.

Abstract: Provided are a computer program product, system, and method for destaging metadata tracks from cache A counter for a metadata track is updated in response to modifying the metadata track in the cache, wherein there are counters for metadata tracks in the cache. The metadata track is destaged from the cache in response to the counter for the metadata track being less than a threshold value. The counter for the metadata track is decremented based on a number of modified metadata tracks in the cache.

Abstract: 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.

Abstract: A method for dynamically balancing I/O workload is disclosed. In one embodiment, such a method includes transmitting, from a host system to a storage system, read requests and write requests over a communication path, such as a zHyperLink communication path. The method further determines whether first and second sets of conditions (e.g., read cache hit ratio, read and write response times, read and write reject rates, etc.) are satisfied on one or more of the host system and storage system. In the event the first set of conditions is satisfied, the method increases a ratio of read requests to write requests that are transmitted over the communication path. In the event the second set of conditions is satisfied, the method decreases the ratio of read requests to write requests that are transmitted over the communication path. A corresponding system and computer program product are also disclosed.

Abstract: 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.

Abstract: In one embodiment, a safe data commit process manages the allocation of task control blocks (TCBs) as a function of the type of task control block (TCB) to be allocated for destaging and as a function of the identity of the RAID storage rank to which the data is being destaged. For example, the allocation of background TCBs is prioritized over the allocation of foreground TCBs for destage operations. In addition, the number of background TCBs allocated to any one RAID storage rank is limited. Once the limit of background TCBs for a particular RAID storage rank is reached, the distributed safe data commit logic switches to allocating foreground TCBs. Further, the number of foreground TCBs allocated to any one RAID storage rank is also limited. Other features and aspects may be realized, depending upon the particular application.

Abstract: A method to dynamically switch between data transfer techniques includes receiving an I/O request and computing a cost of executing the I/O request using a memory copy data transfer technique. The memory copy data transfer technique copies cache segments associated with the I/O request from cache memory to a permanently mapped memory, which is permanently mapped to a bus address window. The method also computes a cost of executing the I/O request using a memory mapping data transfer technique. The memory mapping data transfer technique temporarily maps cache segments associated with the I/O request from the cache memory to the bus address window. The method uses one of the memory copy data transfer technique and the memory mapping data transfer technique to transfer cache segments associated with the I/O request, depending on which one is less costly. A corresponding system and computer program product are also disclosed.

Abstract: A method to dynamically optimize utilization of data transfer techniques includes processing multiple I/O requests using one of several data transfer techniques depending on which data transfer technique is more efficient. The data transfer techniques include: a memory copy data transfer technique that copies cache segments associated with an I/O request from a cache memory to a permanently mapped memory; and a memory mapping data transfer technique that temporarily maps cache segments associated with an I/O request. In order to process the I/O requests, the method utilizes a first number of “copy” windows associated with the memory copy data transfer technique, and a second number of “mapping” windows associated with the memory mapping data transfer technique. The method dynamically adjusts one or more of the first number and the second number to optimize the processing of the I/O requests. A corresponding system and computer program product are also disclosed.

Abstract: A method to dynamically optimize utilization of data transfer techniques includes processing multiple I/O requests using one of several data transfer techniques depending on which data transfer technique is more efficient. The data transfer techniques include: a memory copy data transfer technique that copies cache segments associated with an I/O request from a cache memory to a permanently mapped memory; and a memory mapping data transfer technique that temporarily maps cache segments associated with an I/O request. In order to process the I/O requests, the method utilizes a first number of “copy” windows associated with the memory copy data transfer technique, and a second number of “mapping” windows associated with the memory mapping data transfer technique. The method dynamically adjusts one or more of the first number and the second number to optimize the processing of the I/O requests. A corresponding system and computer program product are also disclosed.

Abstract: Stage task control blocks (TCB) are allocated for performing staging operations in a storage controller controlling one or more storage ranks. Destage TCBs are allocated for performing destaging operations in the storage controller. The storage controller adjusts how many stage TCBs and destage TCBs are to be allocated based on response times of the one or more storage ranks.

Abstract: Provided are techniques for selecting a disconnect from different types of channel disconnects using a machine learning module. An Input/Output (I/O) operation is received from a host via a channel. Inputs are provided to a machine learning module. An output is received from the machine learning module. Based on the output, one of no disconnect from the channel, a logical disconnect from the channel, or a physical disconnect from the channel is selected.

Abstract: A computer program product, system, and method for managing adding of accessed tracks in cache to a most recently used end of a cache list. A cache list for the cache has a least recently used (LRU) end and a most recently used (MRU) end. Tracks in the cache are indicated in the cache list. A track in the cache indicated on the cache list is accessed. A determination is made as to whether a track cache residency time since the accessed track was last accessed while in the cache list is within a region of lowest track cache residency times. A flag is set for the accessed track indicating to indicate the track at the MRU end in response to determining that the track cache residency time of the accessed track is within the region of lowest track cache residency times. The accessed track remains at a current position in the cache list before being accessed after setting the flag.