Described are techniques for processing read and write requests in a system having a NUMA (non-uniform memory access) configuration. Such techniques may include receiving, at a front end adapter of the system, a write request, to write first data to a first storage device, storing a first copy of the first data in first memory local to a first domain, copying, using a first inter-storage processor communication connection, the first data from the first memory to a third memory of a third domain thereby creating a second copy of the first data in the third memory; and determining, in accordance with a first heuristic and first criteria, whether to use the first copy of the first data stored in the first memory or the second copy of the first data stored in the third memory as a source when writing the first data to the first storage device.

An information processing apparatus includes a first memory, and a processor coupled to the first memory and configured to: specify a number of virtual machines executed on each node of a plurality of nodes on an information processing system that performs as a plurality of virtual machines, and calculate a value indicating a degree of deviation of the number of the virtual machines between the plurality of nodes.

Aspects described herein relate to a method comprising: receiving a request to write data to a persistent storage device, the request comprising data; determining an affinity of the data; writing the request to a cache line of a cache; associating the cache line with the affinity of the data; and reporting the data as having been written to the persistent storage device.

Aspects disclosed herein relate to a method comprising: obtaining a list of data paths to at least one persistent storage device through a plurality of NUMA nodes; associating with each data path, access performance information; receiving a request to access one of the at least one persistent storage device; calculating a preferred data path to the one of the at least one persistent storage device using the access performance information; and accessing the one of the at least one persistent storage device using the preferred data path.

Methods and systems for garbage collection are described. In some embodiments, Garbage collector threads may maximize local accesses and minimize remote access by copying Young objects and Old objects differently. When copying a Young object, a garbage collector thread may determine the lgroup of the pool that contains the object and copy the object to a pool of the same lgroup. The garbage collector thread may spread Old objects among lgroups by copying Old objects to pools of the same lgroup as the respective garbage collector thread. Additional methods and systems are disclosed.

The method includes the following steps: step 1. obtaining NUMA topology information of a host machine, and monitoring virtual machine performance events by using a kernel PMU; step 2. implementing a greedy algorithm, and a scheduling decision is obtained; step 3. scheduling, according to the scheduling decision, a virtual CPU (VCPU) and a memory of a virtual machine; step 4. after the scheduling of the virtual machine is complete, redirecting to step 1 to continue performing performance monitoring of the virtual machine.

A data management method wherein a working set is distributed between near and far memories includes migrating first data from the far to the near memory according to a prefetcher algorithm. The first data (a subset of the working set) is maintained in the near memory in data structures according to predetermined semantics of the prefetcher that dictate that certain of the first data is prefetched when a first function evaluates as true. The method further includes detecting that the near memory has reached capacity, and in response, adaptively migrating a portion of the first data out of the near and into the far memory according to an eviction algorithm that is based on the set of prefetcher semantics such that certain of the portion of the first data is evicted when a second function evaluates as true, wherein the second function equals the inverse of the first function.

A data management method is applied to a computing system. The computing system includes a plurality of NUMA nodes, each NUMA node includes a processor and a memory, and each memory is used to store a data block. In the method, a processor in a NUMA node receives an operation request for a data block, and the processor processes the data block, and allocates a replacement priority of the data block in cache space of the NUMA node based on an access attribute of the data block, where the access attribute of the data block includes a distance between a home NUMA node of the data block and the NUMA node.

The present application presents a Uniform Memory Access (UMA) network including a cluster of UMA nodes. A system in a UMA node comprises persistent memory; non-persistent memory, a node control device operatively coupled to the persistent memory and the non-persistent memory, a local interface for interfacing with the local server in the respective UMA node, and a network interface for interfacing with the UMA network. The node control device is configured to translate between a local unified memory access (UMA) address space accessible by applications running on a local server and a global UMA address space that is mapped to a physical UMA address space. The physical UMA address space includes physical address spaces associated with different UMA nodes in the cluster of UMA nodes. Thus, a server in the UMA network can access the physical address spaces at other UMA nodes without going through the servers in the other UMA nodes.

Technologies for quality of service based throttling in a fabric architecture include a network node of a plurality of network nodes interconnected across the fabric architecture via an interconnect fabric. The network node includes a host fabric interface (HFI) configured to facilitate the transmission of data to/from the network node, monitor quality of service levels of resources of the network node used to process and transmit the data, and detect a throttling condition based on a result of the monitored quality of service levels. The HFI is further configured to generate and transmit a throttling message to one or more of the interconnected network nodes in response to having detected a throttling condition. The HFI is additionally configured to receive a throttling message from another of the network nodes and perform a throttling action on one or more of the resources based on the received throttling message. Other embodiments are described herein.