Hewlett Packard Enterprise Development LP

Hewlett Packard Enterprise Patent Development LP

Haris Volos

Kimberly Keeton

Yupu Zhang

Mark David Lillibridge

Milind M Chabbi

James Hyungsun Park

Sanketh Nalli

Evan Randy Kirshenbaum

Goetz Graefe

Sharad Singhal

Harumi Kuno

Jun Li

Ram Swaminathan

Charles Stuart Johnson

Krishnamurthy Viswanathan

Indrajit Roy

Mijung Kim

Henggang Cui

Wey Guy

Pradeep Fernando

Daniel Fryer

Systems and methods for concurrent reading and writing in shared, persistent byte-addressable non-volatile memory is described herein. One method includes in response to initiating a write sequence to one or more memory elements, checking an identifier memory element to determine whether a write sequence is in progress. In addition, the method includes updating an ingress counter. The method also includes adding process identification associated with a writer node to the identifier memory element. Next, a write operation is performed. After the write operation, an egress counter is incremented and the identifier memory element is reset to an expected value.

Concurrent reading and writing with crash recovery in persistent memory

Examples relate to ordering updates for nonvolatile memory accesses. In some examples, a first update that is propagated from a write-through processor cache of a processor is received by a write ordering buffer, where the first update is associated with a first epoch. The first update is stored in a first buffer entry of the write ordering buffer. At this stage, a second update that is propagated from the write-through processor cache is received, where the second update is associated with a second epoch. A second buffer entry of the write ordering buffer is allocated to store the second update. The first buffer entry and the second buffer entry can then be evicted to non-volatile memory in epoch order.

Ordering updates for nonvolatile memory accesses

Exemplary embodiments herein describe programming models and frameworks for providing parallel and resilient tasks. Tasks are created in accordance with predetermined structures. Defined tasks are stored as data objects in a shared pool of memory that is made up of disaggregated memory communicatively coupled via a high performance interconnect that supports atomic operations as descried herein. Heterogeneous compute nodes are configured to execute tasks stored in the shared memory. When compute nodes fail, they do not impact the shared memory, the tasks or other data stored in the shared memory, or the other non-failing compute nodes. The non-failing compute nodes can take on the responsibility of executing tasks owned by other compute nodes, including tasks of a compute node that fails, without needing a centralized manager or schedule to re-assign those tasks. Task processing can therefore be performed in parallel and without impact from node failures.

Programming model and framework for providing resilient parallel tasks

A transformation on raw data is applied to produce transformed data, where the transformation includes at least one selected from among a summary of the raw data or a transform of the raw data between different domains. In response to a query to access data, the query is processed using the transformed data.

Processing a query using transformed raw data

Determining cache value currency using persistent markers is disclosed herein. In one example, a cache entry is retrieved from a local cache memory device. The cache entry includes a key, a value to be used by the computing device, and a marker flag to determine whether the cache entry is current. The local cache memory device also includes a marker location that indicates a location of a marker in a shared persistent fabric-attached memory (FAM). Using a marker location, the marker is retrieved from the shared persistent FAM. From the marker and the marker flag, it is determined whether the cache entry is current. The shared FAM pool is connected to the local cache memory devices of multiple computing devices.

Determining cache value currency using persistent markers

Systems and methods associated with page modification are disclosed. One example method may be embodied on a non-transitory computer-readable medium storing computer-executable instructions. The instructions, when executed by a computer, may cause the computer to fetch a page to a buffer pool in a memory. The page may be fetched from at least one of a log and a backup using single page recovery. The instructions may also cause the computer to store a modification of the page to the log. The modification may be stored to the log as a log entry. The instructions may also cause the computer to evict the page from memory when the page is replaced in the buffer pool. Page writes associated with the eviction may be elided.

Eliding memory page writes upon eviction after page modification

In one example in accordance with the present disclosure, a method may include performing a transactional operation such that if one step of the transactional operation is performed, each other step of the transactional operation is performed. The transactional operation may include making a first copy, stored in a first persistent memory, of a next ticket number stored in a second persistent memory and updating the next ticket number in the second persistent memory. The method may also include determining when to serve a first thread based on the first copy of the next ticket number.

Persistent ticket operation

Examples herein involve fault tolerance in a shared memory. In examples herein, a metadata store of a shared memory indicating versions of data partitions of a resilient distributed dataset and a valid flag for the partitions of the resilient distributed dataset are used to achieve fault tolerance and/or recover from faults in the share memory.

Fault tolerance in shared memory

Examples disclosed herein relate to determining that an operation is accessing data on a persistent memory and retrieving a log of the operation. The examples may also include determining a type of the data being accessed by the persistent memory by the operation and identifying, from the log, a location in the persistent memory of the data accessed by the operation. The examples may also include determining contents of the data accessed by the persistent memory by the operation and determining whether the contents of the data hold an invariant corresponding to the type of data.

Growing community of inventors

Palo Alto, CA, United States of America

Haris Volos