Emc Corporation

Emc IP Holding Company LLC

Steven R Chalmer

Steven T McClure

Brett D Niver

Jonathan I Krasner

Serge Joseph Pirotte

David Reese

Sweetesh Singh

Chakib Ouarraoui

Ian Wigmore

Stephen Smaldone

Uresh K Vahalia

William F Baxter

Avinash Kallat

Stephen D MacArthur

Richard Wheeler

Matthew H Fredette

Kevin Granlund

Matt Fredette

Velmurugan Rathnam

David L Scheffey

Chakib Ourraoui

Techniques for data deduplication may include: receiving write operations that write first data; partitioning the first data into a plurality of data portions; generating, using a first hash function, a plurality of data deduplication hash values for the plurality of data portions, wherein a first data deduplication hash value of the plurality of data deduplication hash values is produced by said generating for a first of the plurality of data portions; performing first processing using a Bloom filter to determine whether the first data deduplication hash value has a corresponding first entry in a data store of deduplication hash values; and responsive to the first processing determining the first data deduplication hash value does not have the corresponding first entry in the data store of deduplication hash values, performing second processing, said second processing including adding the corresponding first entry in the data store of deduplication hash values.

Data deduplication acceleration

A method for processing data includes receiving an offload request by a first virtual machine (VM), issuing, in response to the offload request and based on a processing pipeline, a processing request to a processing unit, and servicing, by the processing unit, the processing request to obtain a result.

Method and system for processing data using a processing pipeline and processing units

A method for processing data includes receiving a write request by a host operating system during a predetermined time window, storing data associated with the write request in a shared memory, making a first determination that a threshold number of write requests are obtained within the predetermined time window, and, in response to the first determination, sending an offload request to a virtual machine (VM), wherein the offload request specifies at least the write request.

Method and system for offloading parallel processing of multiple write requests

A method for processing data includes monitoring, by a virtual machine (VM), a plurality of computing resources, receiving an offload request by the VM, selecting, based on the monitoring, a computing resource from the plurality of computing resources, issuing, by the VM and in response to the offload request, the processing request to the computing resource, and servicing, by the computing resource, the processing request to obtain a result, wherein the VM and the computing resource are executing on a computing device.

Method and system for offloading parity processing

Disclosed are techniques for data deduplication, which include methods, systems, or computer products for reducing data redundancy in a data storage system comprising searching a cluster of nearest neighbors, wherein the cluster has been created using a locality sensitive hashing algorithm, to determine if a data block has been stored in the data storage system prior to writing the data block. In alternate embodiments, the nearest neighbor clusters could be created using one or more of the following algorithms: k-means clustering algorithm, a k-medoids clustering algorithm, a mean shift algorithm, a generalized method of moment (GMM) algorithm, or a density based spatial clustering of applications with noise (DBSCAN) algorithm.

Deduplication using nearest neighbor cluster

Date deduplication acceleration

Embodiments are described for a executing a processing job using one or more nodes of a storage area network using computing resources on the SAN that are predicted to be idle. A predictive model is generated by monitoring idle states of resources of nodes of the SAN and using machine learning to build the predictive model. A scheduler executes jobs on one or more nodes of the SAN with sufficient predicted idle resources to process the job, in accordance with resource requirements and job attributes in a manifest of the job. If a job cannot be completed during a window of time that the necessary resources are predicted to be idle, or if one or more resources become unavailable, the job can be paused and resumed, migrated to another node, or restarted at a later time when the required resources to complete the job are predicted to be idle.

Transient sharing of available SAN compute capability

Operating a hypervisor includes running a hypervisor as a thread of an underlying operating system and loading a guest operating system using the hypervisor based on the thread of the underlying operating system, where the hypervisor runs independently of the guest operating system and independently of other hypervisors running as other threads of the underlying operating system. The hypervisor may be a first hypervisor and operating a hypervisor may further include running a second hypervisor nested with the first hypervisor, where the guest operating system may be loaded using both the first hypervisor and the second hypervisor. The underlying operating system may be an operating system of a storage system.

Nested hypervisors with peripheral component interconnect pass-through

Software emulations of physical devices allow protocol neutral communications between heterogeneous operating systems. Within a computing node of a storage cluster, a logical communications cut-through device connects a guest operating system to a front end adapter and enables the guest operating system to perform operations on an allocated portion of computing node memory without hypervisor intervention. The cut-through device may implement an industry standard memory-mapped interface, thereby enabling a guest operating system to discover the cut-through device and obtain access to memory that is shared with the hypervisor and/or another guest OS. Moreover, if guest OSs and/or the hypervisor share any communications protocol then the channel may be utilized at memory speeds. This may be advantageous in symmetric multiprocessing environments in which multiple guest OSs can have core affinities.

Virtual devices as protocol neutral communications mediators

An interface mitigates the need for inter-application locks in a storage system with a HPP. The interface includes a virtual device driver that can be accessed by both emulation threads and guest OS Container threads and separate memory pages that are pinned for use as buffer spaces. The pinned buffer memory pages are shared by CPU cores and by individual virtual HPP client drivers. The interface enables virtualization of GPUs and HPPs.

GPU virtual device driver for offload processing in a storage array

Data is compressed based on non-identical similarity between a first data set and a second data set. A representation of the differences is used to represent one of the data sets. For example, a probabilistically unique value may be generated as a new block label. Probabilistic comparison of the new block label with a plurality of training labels associated with training blocks produces a plurality of training labels that are potentially similar to the new block label. The Hamming distance between each potentially similar training label and the new block label is determined to select the training label with the smallest calculated Hamming distance from the new block label. A bitmap of differences between the new block and the training block associated with the selected training label is compressed and stored as a compressed representation of the new block.

Data compression by hamming distance categorization

A non-disruptive, non-migratory hypervisor reboot is performed by suspending execution of the guest operating system, rebooting the container, and then resuming execution of the guest operating system. Suspending execution of the guest operating system can include stopping guest OS access to processing resources. Reboot includes the container loading or reloading itself while preserving the contents of the volatile memory in place. It is also possible to relocate some or all of the contents of the volatile memory to different addresses by creating an abstraction layer.

Rebooting a hypervisor without disrupting or moving an associated guest operating system

Methods and systems are disclosed for providing resource sharing in a computing environment using file descriptor isomorphism. The methods and systems may perform a method in a computing environment having processor systems executing processes. The method may include receiving a request from a first process to access a first resource. Further, the method may include generating a first Global File Descriptor (GFD) that references a first entry in a GFD table, the first GFD entry including a reference to a first entry in a resource descriptor table pointing to the first resource. Based on the request, at least one GFD field associated with the first GFD entry is configured. Thus, methods and systems may manage access by the first process to the first resource using the first GFD entry.

Methods and systems for providing resource sharing through file descriptor isomorphism

Methods and systems are disclosed that relate to running a plurality of software instances on an embedded computer system without requiring substantial modifications to each software instance. An exemplary method includes storing context information relating to a first instance. An instance includes a set of independent threads of execution each with its own code context, interrupt service routines, drivers, and operating system services. Both a second instance and a thread associated with the second instance are chosen to run. Context information relating to the second instance is restored and the second instance is run on the operating system.

Methods and systems for allocating hardware resources to instances of software images

Methods and systems are disclosed that relate to handling interrupts across multiple software instances. An exemplary method includes receiving an interrupt at a current CPU. An instance includes a set of independent threads of execution each with its own code context, interrupt service routines, drivers, and operating system services. The method further includes storing context information relating to the first instance, identifying the second instance associated with the interrupt, running at least one interrupt service routine, and restoring the context information relating to the first instance.

Methods and systems for handling interrupts across software instances and context switching between instances having interrupt service routine registered to handle the interrupt

Growing community of inventors

Auburndale, MA, United States of America

Steven R Chalmer