Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.