Hewlett Packard Enterprise Development LP

Susan Agten

Alex Veprinsky

Matthew S Gates

Joel E Lilienkamp

Christopher Robert Sutton

Xiali He

William Michael McCormack

Robert Michael Lester

Example implementations relate to deduplication operations in a storage system. An example implementation includes receiving a data page to be stored in a persistent storage of a deduplication storage system, and, in response to a determination that the data page includes the leading zero pad, performing a circular shift of the plurality of data blocks to generate a realigned data page that begins at a non-zero value portion. The example implementation further includes generating a fingerprint for the realigned data page, and comparing the generated fingerprint to a plurality of fingerprints included in metadata of the deduplication storage system. The example implementation further includes, in response to a determination that no matches are found between the generated fingerprint and the plurality of fingerprints included in the metadata, storing the realigned data page and the generated fingerprint in the persistent storage.

Comparison of a fingerprint generated for a realigned data page that begins at a non-zero value portion to a plurality of fingerprints of a deduplication storage system

Systems and methods are provided for lock-free thread scheduling. Threads may be placed in a ring buffer shared by all computer processing units (CPUs), e.g., in a node. A thread assigned to a CPU may be placed in the CPU's local run queue. However, when a CPU's local run queue is cleared, that CPU checks the shared ring buffer to determine if any threads are waiting to run on that CPU, and if so, the CPU pulls a batch of threads related to that ready-to-run thread to execute. If not, an idle CPU randomly selects another CPU to steak threads from, and the idle CPU attempts to dequeue a thread batch associated with the CPU from the shared ring buffer. Polling may be handled through the use of a shared poller array to dynamically distribute polling across multiple CPUs.

Lock-free work-stealing thread scheduler

Example implementations relate to storing data in a storage system. An example includes receiving, by a storage controller of a storage system, a data unit to be stored in persistent storage of the storage system. The storage controller determines maximum and minimum entropy values for the received data unit. The storage controller determines, based on at least the minimum entropy value and the maximum entropy value, whether the received data unit is viable for data reduction. In response to a determination that the received data unit is viable for data reduction, The storage controller performs at least one reduction operation on the received data unit.

Data reduction in a storage system

In some examples, a system dynamically adjusts a prefetching load with respect to a prefetch cache based on a measure of past utilizations of the prefetch cache, wherein the prefetching load is to prefetch data from storage into the prefetch cache.

Dynamic prefetching of data from storage

Systems and methods are provided for lock-free thread scheduling. Threads may be placed in a ring buffer shared by all computer processing units (CPUs), e.g., in a node. A thread assigned to a CPU may be placed in the CPU's local run queue. However, when a CPU's local run queue is cleared, that CPU checks the shared ring buffer to determine if any threads are waiting to run on that CPU, and if so, the CPU pulls a batch of threads related to that ready-to-run thread to execute. If not, an idle CPU randomly selects another CPU to steal threads from, and the idle CPU attempts to dequeue a thread batch associated with the CPU from the shared ring buffer. Polling may be handled through the use of a shared poller array to dynamically distribute polling across multiple CPUs.

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Boise, ID, United States of America

Susan Agten