International Business Machines Corporation

Globalfoundries Inc.

Lenovo (singapore) Pte. Ltd.

Ecobee Inc.

Sandeep R Patil

Sasikanth Eda

Riyazahamad Moulasab Shiraguppi

Matthew B Trevathan

Gandhi Sivakumar

Sri Ramanathan

Abhinay Ravinder Nagpal

John Thomas Olson

Duane Mark Baldwin

Deepak R Ghuge

John Gerard Musial

Sachin Chandrakant Punadikar

Blaine H Dolph

Bhushan Pradip Jain

Abhishek Jain

Prashant Sodhiya

Dwip N Banerjee

Nataraj Nagaratnam

Dean Hildebrand

Subhojit Roy

Yan Wang Stein

Smita J Raut

Nilesh Prabhakar Bhosale

William W Owen

Dhaval Kiritbhai Shah

Shah M R Islam

Kaustubh I Katruwar

Sandeep Bazar

Pamela Ann Nesbitt

Akshat Mithal

Peter A Balinski

Venkat Venkatsubra

Shah Mohammad R Islam

Matthew Adam Terry

Sreekanth Ramakrishna Iyer

Rahul M Fiske

Bhooshan Prafulla Kelkar

Gaurav Chhaunker

Ranadip Das

Sarbajit Kumar Rakshit

Gail Andrea Spear

Kalyan Chakravarthy Gunda

Pradipta Kumar Banerjee

Ramamohan Chennamsetty

Anbazhagan Mani

Gaurav Mehrotra

Susan L Sylvia

Gregory Tad Kishi

Sarvesh S Patel

Joseph W Dain

Yu-Cheng Hsu

Faried Abrahams

Ranjit Noronha

Ajay K Singh

Carl Evan Jones

Renu Tewari

Ravi Shankar

Lawrence Carter Blount

Guillaume Hoareau

Ashish Pandey

Poornima Gupte

Brian Nelson

Kushal S Patel

Prasenjit Sarkar

Sridhar R Muppidi

Rajeev Kumar Mishra

Shah Mohammad Rezaul Islam

Pankaj S Bavishi

Shripad Jayant Nadgowda

Laurent Sebastien Mignet

Kerard R Hogg

Sriram M Ramanathan

Shrikant V Karve

Janmejay S Kulkarni

Ranjith R Nair

Ashish Chaurasia

Nils Haustein

Vinit Jain

Dirk Pfeiffer

Sangeetha Seshadri

Janice Marie Girouard

Gopal Kumar Bhageria

Eric Philip Fried

Dominic Mueller-Wicke

Wei Gong

Piyush Chaudhary

Daniel Joseph Martin

Mihail Corneliu Constantinescu

Jean-Gael Fabien Reboul

Vijay Dheap

Bhavani Kumar Eshwar

Guang Ya Liu

Umesh Deshpande

Gautam H Shah

Robert J Eggers

Shajeer K Mohammed

Vijayaganesh Subramanian

Andrew John Bernoth

Muthu Annamalai Muthiah

Eran Rom

A computer-implemented method (CIM), according to one embodiment, includes simulating placement of a volume group on a first potential target storage system, and determining a first performance limit for the first potential target storage system based on the simulating. The method further includes predicting a duration the first potential target storage system can host the volume group without performance degradation, based on the first performance limit, and outputting a notification to a customer device, where the notification includes an indication of the predicted duration. A computer program product (CPP), according to another embodiment, includes a set of one or more computer-readable storage media, and program instructions, collectively stored in the set of one or more storage media, for causing a processor set to perform the foregoing method.

Performance-based migration for a volume group

A method for more efficiently storing genomic includes designating multiple different data storage techniques for storing genomic data generated by a genomic pipeline. The method further identifies a file, made up of multiple blocks, generated by the genomic pipeline. The method determines which data storage technique is most optimal to store each block of the file. In doing so, the method may consider the type of the file, the stage of the genomic pipeline that generated the file, the access frequency for blocks of the file, the most accessed blocks of the file, and the like. The method stores each block using the data storage technique determined to be most optimal after completion of a designated stage of the genomic pipeline, such that blocks of the file are stored using several different data storage techniques. A corresponding system and computer program product are also disclosed.

Hybridized storage optimization for genomic workloads

A computer-implemented method for provisioning cloud computing clusters includes receiving a request to create a cloud computing cluster, the cloud computing cluster comprising a clustered filesystem and a requested number of processing nodes and attached storage devices associated with the cloud computing cluster and initiating an initialization process for a single processing node and a corresponding attached storage device responsive to receiving the request to create the cloud computing cluster. The method may also include, previous to completion of the initialization process, requesting and receiving an IP address for the single processing node and a device ID for the corresponding attached storage device from one or more cloud infrastructure controllers and configuring the clustered filesystem and a corresponding WAN cache using the received IP address and the received device ID. A system and computer program product corresponding to the above method are also disclosed herein.

Increasing resource utilization in cloud computing clusters

A computer-implemented method, according to one embodiment, includes: determining, for each pair of HCI systems where each pair includes a first HCI system coupled to another HCI system, a federation relationship setting that corresponds to each pair. The federation relationship settings are used to control a flow of data, as well as to control a flow of workload scheduling, between the first HCI system and the other HCI systems in the respective pairs. Moreover, determining a federation relationship setting that corresponds to a pair includes: determining whether a risk score which corresponds to the pair is outside a predetermined range. In response to determining that the risk score is outside the predetermined range, a restrictive federation relationship setting is assigned to the pair, and in response to determining that the risk score is not outside the predetermined range, a permissive federation relationship setting is assigned to the pair.

Utilizing federation relationship settings among different systems

A computer-implemented method, according to one approach, includes: monitoring actions of a user having access to a cluster, and in response to determining that the user has performed a risk event, incrementing a risk score assigned to the user. A determination is also made as to whether the incremented risk score is outside a predetermined range, and in response to determining that the incremented risk score is outside the predetermined range, a snapshot quota assigned to the user is dynamically reduced.

Dynamically throttling snapshot capture rates

A method for assigning and migrating files among tiers within a unified storage environment. The method includes one or more computer processors determining a plurality of files stored within a tiered storage environment that are accessed by a set executing applications. The method further includes determining that one or more files of the plurality of files are accessed utilizing two or more protocols. The method further includes identifying a group of two or more tiering policies utilized within a tiered storage environment. The method further includes determining protocol-based heat count values corresponding the plurality of files. The method further includes storing the plurality of files among tiers of the tiered storage environment based on the identified group of two or more tiering polices and the protocol-based heat count values corresponding to the plurality of files.

Storage tiering within a unified storage environment

This is an approach to the prediction of soil density and subsoil crop growth. The approach may include subsoil sensor which can monitor changes in soil pressure and moisture conditions. The sensor data can be sent to a computer module which can process the data using a machine learning model predicting the soil density around a subsoil crop and the yield of the subsoil crop. A soil maintenance plan can be generated from the soil density prediction and/or the crop yield prediction. The soil maintenance plan can be sent to soil management robots, which can execute the soil maintenance plan.

Soil density prediction for subsoil crops

A computer-implemented method according to one aspect includes determining and storing characteristics of a plurality of cloud vendors; dividing a workload into a plurality of logical stages; determining characteristics of each of the plurality of logical stages; and for each of the plurality of logical stages, assigning the logical stage to one of the plurality of cloud vendors, based on a comparison of the characteristics of the plurality of cloud vendors to the characteristics of the logical stage. Data migration between the cloud vendors is performed during an implementation of the workload to ensure data is located at necessary cloud vendors during the corresponding tasks of the workload.

Implementing workloads in a multi-cloud environment with data migration between cloud vendors

A processor may identify that an external power source has begun powering a computing device. The processor may identify computational data in a volatile memory of the computing device. The processor may determine that the external power source does not have sufficient energy capacity to provide the computing device enough power to process the computational data at a first I/O throttling rate. The processor may increase the first I/O throttling rate to a second I/O throttling rate. The second I/O throttling rate may allow the computational data to be processed by the computing device with the energy capacity of the external power source.

Increased data storage throttling during power failure

A computer-implemented method according to one embodiment includes compiling log data from all nodes of a cluster, retrieving a timestamp table stored within the cluster, optimizing the timestamp table, and adjusting the log data from all the nodes of a cluster, utilizing the timestamp table.

Synchronizing log data within a cluster

Embodiments of the present invention determine a curiosity of a user based on data received from an electronic device associated with the user, where the data includes audible speech captured from user and one or more facial expressions of the user. Embodiments of the present invention identify a first wavelength for audible speech from the user to initiate a command detection mode based on a plurality of wavelengths associated with a user profile for the user. Embodiments of the present invention identify a topic for the audible speech from the user and responsive to determining an intelligent virtual assistant is an intended recipient based on the topic, suspend an activation word for the intelligent virtual assistant.

Curiosity based activation and search depth

A method for managing commands utilizing command boundaries includes establishing a first command boundary for a first intelligent virtual assistant operating on a first electronic device. The method also includes, responsive to receiving audio from a plurality of sources within a vicinity of the first electronic device, identifying a portion of the audio from the plurality of sources within the first command boundary. The method also includes, responsive to determining a command is identifiable in the portion of the audio from the plurality of sources within the first command boundary, sending the command to the first intelligent virtual assistant on the first electronic device.

Operational command boundaries

A computer-implemented method according to an aspect includes training a cognitive network, utilizing metadata associated with historic data threats, inputting metadata associated with a current data threat into the trained cognitive network, identifying, by the trained cognitive network, one or more stored instances of data determined to be vulnerable to the current data threat, and adjusting one or more security aspects of the one or more stored instances of data determined to be vulnerable to the current data threat.

Protecting data based on a sensitivity level for the data

A data storage system has multiple tiers of data storage including an upper tier having a lower access latency and a lower tier having a higher access latency. A storage controller of the data storage system receives, via an interface, an access request of a workload for a target file system object, where the target file system object has an associated temperature. In response to the access request for the target file system object, the storage controller accesses the target file system object in the data storage and conditions update of the associated temperature of the target file system object based on at least one of a set including the interface and the workload. The storage controller distributes a collection of file system objects including the target file system object among the multiple tiers based on respective heats of file system objects in the collection.

Workload and interface cognizant heat-tiered storage

A computer-implemented method, according to one embodiment, includes: receiving one or more suggestions which correspond to placement of data in storage, where the one or more suggestions are based on data workload characteristics. The one or more suggestions are used to identify portions of actual data stored in actual storage which correspond to the one or more suggestions. For each of the identified portions of the actual data stored in the first tier, the one or more suggestions is further used to determine whether to transfer the given identified portion of the actual data to the second tier. Moreover, in response to determining to transfer at least one of the identified portions of the actual data to the second tier, one or more instructions are sent to transfer the at least one of the identified portions of the actual data from the first tier to the second tier.

Increasing data performance by transferring data between storage tiers using workload characteristics

Growing community of inventors

Pune, India

Sandeep R Patil