Emc IP Holding Company LLC

Adaptec, Inc.

Sassan Teymouri

Sorin Faibish

John Michael Bent

James M Pedone, Jr

Salil Suri

Dennis P Ting

Dominique P Cote

Dennis Pei Jean Ting

A cluster file system comprises a front-end file system, a back-end file system, data mover modules arranged between the front-end and back-end file systems, and a quota manager associated with at least a given one of data mover modules. The data mover modules are configured to control archiving of data between the front-end file system and the back-end file system for respective users based at least in part on respective user quotas established by the quota manager and identifying corresponding portions of the back-end file system available to the users. The front-end file system may comprise archive directories configured for respective ones of the users, with the data mover modules being configured to archive a given file from the front-end file system in the back-end file system responsive to a link to that file being stored in a corresponding one of the archive directories of the front-end file system.

Cluster file system comprising data mover modules having associated quota manager for managing back-end user quotas

An apparatus in one embodiment comprises a cloud-based web object indexing platform configured to communicate with multiple web servers over at least one network. The cloud-based web object indexing platform comprises a plurality of indexing applications having respective machine learning engines, with a given one of the indexing applications being configured to receive web objects over the network from one or more of the web servers and to process the received web objects utilizing its corresponding machine learning engine. The given indexing application is further configured to generate semantic information for association with particular ones of the web objects based at least in part on processing results provided by the corresponding machine learning engine. The semantic information is made accessible by the cloud-based web object indexing platform in association with the particular web objects over the network, for example, to a search engine or data analytics engine.

Cloud-based platform for semantic indexing of web objects

An apparatus in one embodiment comprises a storage system having a plurality of object storage servers. A software-defined storage controller of the storage system configures a unified memory cluster accessible to each of the plurality of object storage servers. The object storage servers collectively implement a distributed tiered parallel file system, such as a distributed tiered Lustre file system. The unified memory cluster may comprise portions of respective flash memories of a plurality of nodes of the storage system where each of the nodes comprises a corresponding one of the object storage servers. Objects stored in the flash memory of one of the nodes are mirrored into the flash memories of one or more other ones of the nodes under the control of the software-defined storage controller.

Storage system with distributed tiered parallel file system comprising software-defined unified memory cluster

A System, Computer program product, and computer-executable method of dynamically modifying data storage resilience within a two tiered data storage system, where the two tiered data storage system includes one or more fast data storage appliances and storage capacity tier wherein the fast data storage appliance is enabled to provide reliable data storage, the System, Computer program product, and computer-executable method including receiving configuration information from a node utilizing the two-tiered data storage system, wherein the configuration information provides characteristics of a job, analyzing the configuration information, updating use of the fast data storage appliances based on the analysis.

Dynamic resilience in flash acceleration tiers

An apparatus in one embodiment comprises a multi-tier storage system and at least one dispatcher node. The multi-tier storage system comprises at least a front-end storage tier and a back-end storage tier. The at least one dispatcher node is configured to load portions of graph data from the front-end storage tier and the back-end storage tier for graph analytics computations performed at respective ones of a plurality of compute nodes configured for communication with the storage system over at least one network. The multi-tier storage system configured to switch logical connections of respective ones of the compute nodes to the at least one dispatcher node based on progress of graph analytics computations at the compute nodes.

Multi-tier storage system having a front-end storage tier facilitating efficient graph analytics computations

An apparatus in one embodiment comprises a plurality of compute nodes each having a processor coupled to a memory. The apparatus further comprises a storage system configured for communication with the compute nodes over at least one network, with the storage system comprising a software-defined storage controller configured to implement an in-memory database accessible as a unified memory cluster to respective processors of the compute nodes. The in-memory database comprises portions of respective memories of the compute nodes. The in-memory database may be expanded, for example, using an additional portion of the memory of one of the compute nodes, responsive to an overflow event associated with the memory of another one of the compute nodes. The compute nodes may illustratively comprise respective analysis nodes that run respective applications configured to utilize analytics functionality of the in-memory database. Other illustrative embodiments include systems, methods and processor-readable storage media.

In-memory database with memory clustering utilizing software-defined storage functionality

An information processing system comprises a plurality of front-end storage tiers, a plurality of back-end storage tiers, a plurality of data mover modules arranged between the front-end and back-end file storage tiers, and a metadata warehouse associated with the data mover modules and the front-end and back-end storage tiers. The data mover modules are configured to control movement of data between the storage tiers. The metadata warehouse is configured to store for each of a plurality of data items corresponding metadata comprising movement information characterizing movement of the data item between the storage tiers. The movement information for a given data item illustratively comprises locations, timestamps and checksums for different stages of movement of the given data item. Other types of metadata for the given data item illustratively include lineage information, access history information and compliance information.

System comprising front-end and back-end storage tiers, data mover modules and associated metadata warehouse

A time domain signal filter detects a change in an input signal and replaces the input signal with an internally generated substitute signal for a filter period. The filter period is user selectable and can be set through a bit in a hardware register. After passage of the filter period, the time domain signal filter resumes direct supply of the input signal as the output signal. The time domain signal filter determines the start of the filter period by using either the falling edge or the rising edge of the clock input, whichever edge comes first after detecting the change in the input signal.

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Saratoga, CA, United States of America

Sassan Teymouri