Hewlett Packard Enterprise Development LP

Hewlett-packard Company

Hewlett-packard Development Company, L.p.

Douglas L Voigt

Suparna Bhattacharya

Michael B Jacobson

Marvin D Nelson

Theresa A Burkes

Wade A Dolphin

Kalapriya Kannan

Boris Zuckerman

Bryan M Diamond

Dejan S Milojicic

Randy Matthews

Harold Woods

Muthukumar Murugan

Meng Zou

Neeraj Gokhale

Richelle L Ahlvers

Don L Burkes

Kirk A Hanson

Gregg Bernard Lesartre

Joseph Foster

John Wilkes

Siamak Nazari

Russ William Herrell

Michael R Krause

Robert A Rust

Andrew Christopher Walton

Alistair Veitch

David William Thiel

James S Jackson

Dhruva Ranjan Chakrabarti

Daniel Juergen Gmach

Sandya Srivilliputtur Mannarswamy

James Michael Reuter

Robert Baird

Ayman Abouelwafa

Brian Patterson

Alex Veprinsky

Charles B Morrey, Iii

Vitaly M Oratovsky

Douglas James Cameron

Greg Astfalk

Jishen Zhao

Douglas L Hagerman

Mohamed Belhadj

Marc Edward LeFevre

Ronald D Rodriguez

Timothy Mosier

Randy J Matthews

Carl H Staelin

Michael E Lutz

David Alan Daigle

Donald E Bollinger

Ancy Sarah Tom

Charles Franklin Randall

David J Hoover

Bernard A Reed, Iii

Marjorie Krueger

Scott Grumm

Christian A Kimoto

Bruce A Olsen

Hamid Vazire

John W Fordemwalt

Susan L Larson

Steven D Messinger

Timothy T Sullivan

Examples include bypassing a portion of an analytics workflow. In some examples, execution of an analytics workflow may be monitored upon receipt of a raw data and the execution may be interrupted at an optimal bypass stage to obtain insights data from the raw data. A similarity analysis may be performed to compare the insights data to a stored insights data in an insights data repository. Based, at least in part, on a determination of similarity, a bypass operation may be performed to bypass a remainder of the analytics workflow.

Similarity analyses in analytics workflows

An example implementation may relate to an apparatus that may identify data content of interest from data in buffers, and may store index entries representing the identified data content in a hierarchical index having different performance levels. The apparatus may include a priority manager that maintains an index scoreboard that tracks where index entries are to be stored among the different performance levels of the hierarchical index based on predetermined polices that prioritize data content of interest or functions that use data content of interest.

Hierarchical index involving prioritization of data content of interest

Some examples relate to associating an insight with data. In an example, data may be received. A determination may be made that data type of the data is same as compared to an earlier data. An insight generated from the earlier data may be identified, wherein the insight may represent intermediate or resultant data generated upon processing of the earlier data by an analytics function, and wherein during generation metadata is associated with the insight. An analytics function used for generating the insight may be identified.

Associating insights with data

Examples disclosed herein relate to a storage appliance using an optimistic allocation of storage space. In an example system, a number of storage drives are coupled to a storage controller and a RNIC (remote direct memory access (RDMA) network interface card (NIC)) through a storage network. The RNIC includes a layout template selector and a plurality of templates. The layout template selector selects a layout template based, at least in part, on a logical block address (LBA) received from a host. The layout template identifies each of a number of storage drives associated with portions of data represented by the LBA. The controller includes a virtualization computation module to determine a new layout template for the data represented by the LBA and the new layout template.

Determining layout templates identifying storage drives

Examples disclosed herein relate to a storage appliance using an optimistic allocation of storage space. In an example system, a number of storage drives are coupled to a storage controller and an RNIC (remote direct memory access (RDMA) network interface card (NIC)) through a storage network. The RNIC includes a layout template selector and a number of templates. The layout template selector selects a template based, at least in part, on a logical block address (LBA) received from a host. The template identifies each of a plurality of storage drives in the plurality of storage drives associated with portions of data represented by the LBA. A slave drive in the number of storage drives includes a state indicator that indicates the status of a transaction. A master drive in the number of storage drives also includes the state indicator to indicate the status of the transaction.

Flushes based on intent log entry states

Relevance optimized representative content associated with a data storage system is disclosed. One example is a system including a data summarization module, a clustering module, and a representative content selection module. The data summarization module associates, via a processor, each data object in a storage system with a derived data object. The clustering module determines clusters of similar data objects based on a similarity between associated derived data objects, and selects a representative data object for each determined cluster. The representative content selection module selects representative content associated with the storage system, where the representative content is based on the data objects, the derived data objects, and the representative data objects, and relevance optimizes of the selected representative content to an analytics application.

Relevance optimized representative content associated with a data storage system

Examples disclosed herein relate to a storage appliance using an optimistic allocation of storage space. In an example system, a number of storage drives are coupled to a storage controller and an RNIC (remote direct memory access (RDMA) network interface card (NIC)) through a storage network. The RNIC includes a layout template selector and a number of templates, wherein the layout template selector selects a template based, at least in part, on a logical block address (LBA) received from a host. The template identifies each of the plurality of storage drives associated with portions of data represented by the LBA.

Remote direct memory access

Various examples described herein provide for migrating a file between a non-persistent memory file system and a persistent memory file system. In particular, some examples detect, on a non-persistent memory file system, a file that has been memory-mapped while being accessed from the non-persistent memory file system by a computer system, and the detected file is migrated from the non-persistent memory file system to the persistent memory file system.

File migration to persistent memory

A plurality of mapping modes may be shifted between in real time while maintaining continuous memory mapped access to an application. Data may be migrated between different types storage devices and/or interconnects. The shift between the plurality of mapping modes may be based on a change to the type storage device and/or type of interconnect for the data migration.

Mapping mode shift between mapping modes that provides continuous application access to storage, wherein address range is remapped between said modes during data migration and said address range is also utilized bypass through instructions for direct access

Embodiments herein relate to selecting an application server to nonvolatile random access memory (NVRAM) path. The path provides direct access between an application server and the NVRAM. The path is to transmit data related to at least one of a read and write request to a virtual memory of the application server.

Application server to NVRAM path

Various examples described herein provide for caching a page on persistent memory for memory-mapped access of a file from a non-persistent memory file system or a remote file system having a non-persistent memory page cache. In particular, some examples detect memory-mapped access of a file from a non-persistent memory file system or a remote file system having a non-persistent memory page cache and, based on availability of persistent memory, caches a page associated with the memory-mapped access on the persistent memory.

Page cache on persistent memory

Example implementations relate to performing computations using provenance data. An example implementation includes storing first lineage data of a first dataset and provenance data of an application operating on the first dataset in a storage system. A computing resource may determine whether second lineage data of a second dataset meets a similarity criterion with the first lineage data of the first dataset. A computation on the second dataset may be performed using the provenance data of the application, and an insight of the second dataset may be generated from the performed computation.

Performing a computation using provenance data

An example implementation in accordance with an aspect of the present disclosure includes an address translation table of a transparent router. In response to an add service request to add a service to at least a portion of a memory system, a first address to be affected by the service is identified. An affected entry of an address translation table of the transparent router is also identified. The affected entry corresponds to a data path including the first address. The affected entry is modified to cause its corresponding data path to point to a second address associated with the service.

Transparent routers to provide services

Examples disclosed herein relate to data provisioning for an analytical process based on lineage metadata. In an example, a value of a parameter related to execution of an analytical process on a remote hub device may be determined based on lineage metadata stored on an edge device, wherein the analytical process is part of an analytical workflow that may be implemented at least in part on the edge device and the remote hub device. In response to a determination that the value of the parameter is above a predefined threshold, the edge device may provide to the remote hub device, input data for a future execution of the analytical process in advance of execution of the analytical process on the remote hub device without a request for the input data by the remote hub device.

Data provisioning for an analytical process based on lineage metadata

Growing community of inventors

Boise, ID, United States of America

Douglas L Voigt