Emc IP Holding Company LLC

Emc Corporation

Dell Products Inc.

Other

Philippe Armangau

Jean-Pierre Bono

Vamsi K Vankamamidi

Christopher Alan Seibel

William C Davenport

Sorin Faibish

Ivan Bassov

Yubing Wang

Istvan Gonczi

Ajay Karri

Sitaram D Pawar

Ahsan Rashid

Stephen J Todd

Xiangping Chen

Walter Forrester

Ivan Basov

Miles Aram De Forest

Bruce E Caram

Yining Si

Geng Han

Ashok Tamilarasan

Monica Chaudhary

Rohit K Chawla

Dennis Thomas Duprey

John F Gillono

Daniel E Cummins

Alexander S Mathews

Maher Kachmar

Jian Gao

Michael Kilian

Karl M Owen

Yingchao Zhou

Mark K Ku

Diane Delgado

Philip N Shilane

Anton Kucherov

Himabindu Tummala

Feng Zhang

Sairam Veeraswamy

Xinlei Xu

Junping Zhao

James M Pedone, Jr

Shuyu Lee

Socheavy D Heng

Ye Zhang

Milena Bergant

Steven A Morley

Frederic Corniquet

Michal Marko

Yaming Kuang

Rustem Rafikov

Wai Chuen Yim

John Forecast

Morgan A Clark

Srinivasa Rao Vempati

Marc DeSouter

Vasu Subramanian

Alexei Karaban

Kamakshi Viswanadha

Fenghao Zhang

Hongpo Gao

Yousheng Liu

Uday K Gupta

David W Harvey

Alan Lee Taylor

Xiaoye Jiang

Uresh K Vahalia

Richard P Ruef

Nagasimha G Haravu

Marc A De Souter

Peter C Bixby

Michael P Wahl

Dixitkumar Vishnubhai Patel

Vasudevan Subramanian

Ruiling Dou

Xianlong Liu

Kumari Bijayalaxmi Nanda

Pranit Sethi

Soumyadeep Sen

Michael Scheer

Henry Austin Spang, Iv

Jia Zhai

Michael D Schouten

Arieh Don

Vladimir Shveidel

Owen Martin

Amitai Alkalay

John Michael Bent

Shaoqin Gong

Ronen Gazit

Jamin Jianbin Kang

Tomer Shachar

Baote Zhuo

Matthew H Long

Jun Guo

John Michael Hayden

Samuel L Mullis, Ii

Mukesh Gupta

Xunce Zhou

Karthikeyan Srinivasan

A system can determine to generate error correction codes for a storage system that comprises computing nodes. The system can logically divide the computing nodes into disjunctive subsets. The system can, for each disjunctive subset, create a partition, and identify a group of elements that comprises sub-strips of the disjunctive subset. The system can add a first element from each disjunctive subset of the disjunctive subsets to the partition, and removing the first element from the group of elements. The system can, for each disjunctive subset, add a second element from the group of elements along with elements stored in parity notes of a sub-strip where the second element is located. The system can, in response to determining that a number of elements of the disjunctive subset is at least as large as a number of the computing nodes, create the error correction codes based on the elements.

HashTag codes for reduced repair bandwidth

A method, computer program product, and computer system for receiving, by a computing device, a write request, wherein the write request may be received by a file system of the computing device. Data associated with the write request may be stored in a cache of the file system and a cache of a block storage system corresponding to the file system. A tag associated with the data in the cache of the block storage system may be received by the block storage system. The data in the cache of the block storage system may be freed after flushing the data to persistent storage based upon, at least in part, the tag associated with the data in the cache of the block storage system. As a result, there is optimization for the read path due to no double caching in the block cache.

Systems and methods for cooperative caching between file systems and block storage

A technique for managing a mapping structure in a data storage system includes identifying levels in the mapping structure of pages to be removed and estimating the workload required for removing the pages based at least in part on the identified levels. The technique further includes initiating processing of the pages based at least in part on the estimated workload.

Processing pages marked for deletion

Techniques for providing host applications the ability to dynamically manage application-specific functionality of storage applications. The techniques include providing, on a storage system, a storage application such as a data object processing pipeline including a series of pipeline elements (PEs), and receiving, at the storage system from a host computer, a command containing parameters for configuring an application of a specified PE from among the series of PEs. The techniques further include, in response to receipt of the command, configuring, by the storage system, the application of the specified PE based on the parameters contained in the command, executing the data object processing pipeline including the application of the specified PE on end-user data, and sending, by the storage system to the host computer, a command containing verification information pertaining to execution of the data object processing pipeline and/or information pertaining to processing or memory resources of the storage system.

Provide host applications ability to dynamically manage application specific functionality on storage application

A method of managing CPU cores in a data storage apparatus (DSA) configured to perform both host I/O (Input/Output) processing and background storage processing is provided. The method includes (a) selectively classifying background storage tasks in one of a first classification for longer-running tasks and a second classification for shorter-running tasks; (b) selecting CPU cores that are running fewer than a threshold number of first-classification background tasks to process host I/O requests; and (c) processing the host I/O requests on their selected CPU cores. An apparatus, system, and computer program product for performing a similar method are also provided.

Techniques for managing cores for storage

A power controller for a data storage system automatically selects different power modes based on changing forecasts of availability of renewable energy. The power modes indicate settings for each of a plurality of hardware resources, such as processors, fans, memory, and drives. At times when the storage system can operate at less than the maximum level of performance in terms of IO latency or IOPS, power consumption of one or more of the hardware resources is reduced to a degree corresponding to availability of renewable energy. For example, the hardware resources may be operated in a relatively higher power mode when renewable energy is available than when renewable energy is unavailable. The storage system may be configured to automatically implement a low power mode when power from all sources is in limited supply, e.g., during a brownout.

Autonomous power management for sustainable storage

One or more aspects of the present disclosure relate to enhancing modular device snapshot-to-encryption-key associations. In embodiments, an input/output (IO) workload can be received at a storage array. The IO workload can include an IO request to write encrypted data on the storage array. The IO request's metadata can also be parsed for information such as snap parameters. Further, an encryption key identifier (ID) can be received from a host, and snapshots of a storage unit can be created with the parsed information and the key ID.

Encryption key enhancement of storage array snapshots

Techniques for supporting a native pipeline element abstract for use in processing and storing data objects in a storage environment. The techniques include providing a data object processing pipeline for execution on a storage system, ingesting, by the data object processing pipeline, data objects collected by a plurality of computerized devices coupled to the storage system, performing queuing and processing of the data objects at a series of processing elements of the data object processing pipeline, and providing the processed data objects from the storage system to a host computer for subsequent use or analysis. In this way, the number of storage requests needed to be handled by the storage system can be reduced. Moreover, because the data object processing pipeline can be implemented and executed on the storage system, the processing and storage of data objects in the storage environment can be performed more efficiently and optimized more easily.

Native pipeline element abstract support in storage system

Rebalancing the workload of logical devices across multiple nodes may include dynamically modifying preferred paths for one or more logical devices in order to rebalance the I/O workload of the logical devices among the nodes of the data storage system. Determining whether to rebalance the I/O workload between the two nodes may be performed in accordance with one or more criteria. Processing may include monitoring the current workloads of both nodes over time and periodically evaluating, in accordance with the one or more criteria, whether the current workloads of the nodes are imbalanced. Responsive to determining, in accordance with the criteria, that rebalancing of workload between the nodes is needed, the rebalancing may be performed. A notification may be sent to the host regarding any path state changes made as a result of the workload rebalancing.

Techniques for workload balancing using dynamic path state modifications

A data storage system can include a deduplicated data cache used to store unique deduplicated data portions. Data portions can be promoted to the deduplicated data cache in connection with servicing I/O operations. Servicing the I/O operation that reads data from, or writes data to, a logical address can include determining whether a data portion stored at the logical address meets criteria for promoting the data portion to a deduplicated data cache. The criteria can include a condition that the data portion is a duplicate of content stored at multiple logical addresses, and can include a condition that the data portion has a reference count that is at least a minimum threshold where the reference count denotes a number of logical addresses at which the data portion is stored. Responsive to determining the data portion meets the criteria, the data portion can be stored in the deduplicated data cache.

Caching techniques using a data deduplication cache and a data cache

A technique of protecting data from ransomware attacks identifies a set of blocks written to a data object between first and second points in time, determines a set of attributes of the set of blocks, and, in response to the set of attributes indicating a likelihood of a ransomware attack, secures a state of the data object as of the first point in time.

Block-based protection from ransomware

A technique for achieving data mobility between storage systems having different block sizes includes identifying a baseline size that is common to the block sizes of the storage systems. The technique further includes generating fingerprints of blocks based on extents having the common baseline size. Fingerprint-based data mobility is then achieved by comparing extent-based fingerprints, or combinations thereof, across different storage systems to identify matching data.

Fingerprint-based data mobility across systems with heterogenous block sizes

A method, computer program product, and computing system for defining a quantity of discrete storage portions within a storage system; entering an expansion mode during which the discrete storage portions are incrementally assigned to at least one processing node until a first assignment level target is achieved; once the first assignment level target is achieved, entering a utilization mode during which the utilization of the assigned discrete portions is increased until a first utilization level target is achieved; and once the first utilization level target is achieved, reentering the expansion mode during which additional discrete storage portions are incrementally assigned to the at least one processing node until a second assignment level target is achieved.

Memory management system and method

Techniques for rebuilding space accounting counters in mapping layers of storage appliances. The techniques include uniquely associating top levels of a mapping layer of a storage appliance with respective storage objects. The techniques further include determining amounts of logical storage space consumed by the respective storage objects from mappings of LBAs of the respective storage objects to virtual blocks of a virtual layer of the storage appliance. The techniques further include determining amounts of physical storage space consumed by the respective storage objects from logged information pertaining to each leaf pointer of a leaf level of the mapping layer that points to a virtual block in the virtual layer, each virtual block being mapped to a physical block in a physical layer of the storage appliance. The techniques further include using multi-threading to determine amounts of logical storage space consumed by dynamically adjustable ranges of the respective storage objects.

Rebuilding space accounting counters in mapping layer of storage appliances

A technique for performing data deduplication operates at sub-block granularity by searching a deduplication database for a match between a candidate sub-block of a candidate block and a target sub-block of a previously-stored target block. When a match is found, the technique identifies a duplicate range shared between the candidate block and the target block and effects persistent storage of the duplicate range by configuring mapping metadata of the candidate block so that it points to the duplicate range in the target block.

Deduplicating data at sub-block granularity

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Acton, MA, United States of America

Philippe Armangau