Patents by Inventor Koushik K. Das
Koushik K. Das has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11169592Abstract: For power management in a disaggregated computing system, upon detecting an electrical power reduction to the disaggregated computing system, respective workloads being performed by respective processors within a set of processors are prioritized according to a service level agreement (SLA) of the respective workloads. Backup electrical power is dynamically allocated to the respective processors performing the respective workloads based upon a priority of the SLA of the respective workloads.Type: GrantFiled: October 10, 2016Date of Patent: November 9, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 11153223Abstract: Server resources in a data center are disaggregated into shared server resource pools. Servers are constructed dynamically, on-demand and based on workload requirements, by allocating from these resource pools. A disaggregated compute system of this type keeps track of resources that are available in the shared server resource pools, and it manages those resources based on that information. Each server entity built is assigned with a unique server ID, and each resource that comprises a component thereof is tagged with the identifier. As a workload is processed by the server entity, its composition may change, e.g. by allocating more resources to the server entity, or by de-allocating resources from the server entity. Workload requests are associated with the unique server ID for the server entity. When a workload request is received at a resource, it matches its unique server ID to that of the request before servicing the request.Type: GrantFiled: April 7, 2016Date of Patent: October 19, 2021Assignee: International Business Machines CorporationInventors: Valentina Salapura, John Alan Bivens, Koushik K. Das, Min Li, Ruchi Mahindru, Harigovind V. Ramasamy, Yaoping Ruan, Eugen Schenfeld
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Patent number: 10884821Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.Type: GrantFiled: June 20, 2019Date of Patent: January 5, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10838482Abstract: For power management in a disaggregated computing system, initial electrical power levels are distributed thereby allocating a voltage and a clock speed to each one of a set of processor cores in the disaggregated computing system. The voltage and the clock speed of respective processor cores within the set of processor cores are adjusted according to a workload priority of respective workloads performed by each respective one of the processor cores, wherein the workload priority is assigned based upon a service level agreement (SLA).Type: GrantFiled: October 10, 2016Date of Patent: November 17, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10819599Abstract: For measuring component utilization in a system having a plurality of subsystems, an energy consumption of each of the plurality of subsystems is monitored whether or not each subsystem performs at least a portion of an overall computation. Respective workloads are classified based upon an energy consumption pattern associated with the monitored energy consumption of each of the plurality of subsystems.Type: GrantFiled: October 10, 2016Date of Patent: October 27, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10545560Abstract: For power management in a computing system, component utilization is dynamically managed within the computing system according to a calculated aggregate energy consumed by each one of a set of processors. Each of a plurality of energy factors are measured individually between each one of the set of processors to accumulate the calculated aggregate energy in real time.Type: GrantFiled: October 10, 2016Date of Patent: January 28, 2020Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Publication number: 20190310897Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.Type: ApplicationFiled: June 20, 2019Publication date: October 10, 2019Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Patent number: 10409509Abstract: A memory management service occupies a configurable portion of an overall memory system in a disaggregate compute environment. The service provides optimized data organization capabilities over the pool of real memory accessible to the system. The service enables various types of data stores to be implemented in hardware, including at a data structure level. Storage capacity conservation is enabled through the creation and management of high-performance, re-usable data structure implementations across the memory pool, and then using analytics (e.g., multi-tenant similarity and duplicate detection) to determine when data organizations should be used. The service also may re-align memory to different data structures that may be more efficient given data usage and distribution patterns. The service also advantageously manages automated backups efficiently.Type: GrantFiled: November 3, 2017Date of Patent: September 10, 2019Assignee: International Business Machines CorporationInventors: John Alan Bivens, Koushik K. Das, Min Li, Ruchi Mahindru, Harigovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10401940Abstract: For power management in a disaggregated computing system, a set of initial electrical power levels are allocated to a set of processor cores according to a predicted desired workload, where the set of initial power levels aggregate to an initial collective contracted power level. Electrical power is dynamically allocated to respective processor cores within the set of processor cores to produce a capacity to execute a collective demanded workload while maintaining the electrical power to the set of processor cores to an approximately constant electrical power level within a threshold of the initial collective contracted electrical power level.Type: GrantFiled: October 10, 2016Date of Patent: September 3, 2019Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10360077Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.Type: GrantFiled: October 10, 2016Date of Patent: July 23, 2019Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi Mahindru, John A. Bivens, Koushik K. Das, Min Li, HariGovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 10171375Abstract: Various embodiments for allocating resources in a disaggregated cloud computing environment, by a processor device, are provided. Respective members of a pool of hardware resources are assigned to each one of a plurality of tenants based upon a classification of the respective members of the pool of hardware resources. The respective members of the pool of hardware resources are assigned to each one of the plurality of tenants independently of a hardware enclosure in which the respective members of the pool of hardware resources are physically located.Type: GrantFiled: April 21, 2016Date of Patent: January 1, 2019Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Yaoping Ruan, John A. Bivens, Koushik K. Das, Min Li, Ruchi Mahindru, HariGovind V. Ramasamy, Valentina Salapura, Eugen Schenfeld
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Patent number: 10129169Abstract: Server resources in a data center are disaggregated into shared server resource pools. Servers are constructed dynamically, on-demand and based on workload requirements and a tenant's resiliency requirements (e.g., as specified in an SLA), by allocating from these resource pools. A disaggregated compute system of this type keeps track of resources that are available in the shared server resource pools, and it manages those resources based on that information and the health of the resources. As a workload is processed by the server entity and component resources fail, the server entity composition is changed, e.g. by allocating other resources to the server entity, or by transitioning to other server entities, to ensure that a resiliency requirement is maintained.Type: GrantFiled: April 7, 2016Date of Patent: November 13, 2018Assignee: International Business Machines CorporationInventors: Ruchi Mahindru, John Alan Bivens, Koushik K. Das, Min Li, Harigovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Publication number: 20180101214Abstract: For power management in a disaggregated computing system, initial electrical power levels are distributed thereby allocating a voltage and a clock speed to each one of a set of processor cores in the disaggregated computing system. The voltage and the clock speed of respective processor cores within the set of processor cores are adjusted according to a workload priority of respective workloads performed by each respective one of the processor cores, wherein the workload priority is assigned based upon a service level agreement (SLA).Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180101220Abstract: For power management in a disaggregated computing system, a set of initial electrical power levels are allocated to a set of processor cores according to a predicted desired workload, where the set of initial power levels aggregate to an initial collective contracted power level. Electrical power is dynamically allocated to respective processor cores within the set of processor cores to produce a capacity to execute a collective demanded workload while maintaining the electrical power to the set of processor cores to an approximately constant electrical power level within a threshold of the initial collective contracted electrical power level.Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180101215Abstract: For power management in a disaggregated computing system, upon detecting an electrical power reduction to the disaggregated computing system, respective workloads being performed by respective processors within a set of processors are prioritized according to a service level agreement (SLA) of the respective workloads. Backup electrical power is dynamically allocated to the respective processors performing the respective workloads based upon a priority of the SLA of the respective workloads.Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180102953Abstract: For measuring component utilization in a system having a plurality of subsystems, an energy consumption of each of the plurality of subsystems is monitored whether or not each subsystem performs at least a portion of an overall computation. Respective workloads are classified based upon an energy consumption pattern associated with the monitored energy consumption of each of the plurality of subsystems.Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180101216Abstract: For power management in a computing system, component utilization is dynamically managed within the computing system according to a calculated aggregate energy consumed by each one of a set of processors. Each of a plurality of energy factors are measured individually between each one of the set of processors to accumulate the calculated aggregate energy in real time.Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180101415Abstract: For measuring component utilization in a computing system, a server energy utilization reading of a statistical significant number of servers out of a total number of servers located in the datacenter is obtained by measuring, at predetermined intervals, a collective energy consumed by all processing components within each server. The collective energy is measured by virtually probing thereby monitoring an energy consumption of individual ones of all the processing components to each collect an individual energy utilization reading, where the individual energy utilization reading is aggregated over a predetermined time period to collect an energy consumption pattern associated with the server utilization reading.Type: ApplicationFiled: October 10, 2016Publication date: April 12, 2018Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ruchi MAHINDRU, John A. BIVENS, Koushik K. DAS, Min LI, HariGovind V. RAMASAMY, Yaoping RUAN, Valentina SALAPURA, Eugen SCHENFELD
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Publication number: 20180074741Abstract: A memory management service occupies a configurable portion of an overall memory system in a disaggregate compute environment. The service provides optimized data organization capabilities over the pool of real memory accessible to the system. The service enables various types of data stores to be implemented in hardware, including at a data structure level. Storage capacity conservation is enabled through the creation and management of high-performance, re-usable data structure implementations across the memory pool, and then using analytics (e.g., multi-tenant similarity and duplicate detection) to determine when data organizations should be used. The service also may re-align memory to different data structures that may be more efficient given data usage and distribution patterns. The service also advantageously manages automated backups efficiently.Type: ApplicationFiled: November 3, 2017Publication date: March 15, 2018Applicant: International Business Machines CorporationInventors: John Alan Bivens, Koushik K. Das, Min Li, Ruchi Mahindru, Harigovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld
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Patent number: 9916636Abstract: Server resources in a data center are disaggregated into shared server resource pools, including a graphics processing unit (GPU) pool. Servers are constructed dynamically, on-demand and based on workload requirements, by allocating from these resource pools. According to this disclosure, GPU utilization in the data center is managed proactively by assigning GPUs to workloads in a fine granularity and agile way, and de-provisioning them when no longer needed. In this manner, the approach is especially advantageous to automatically provision GPUs for data analytic workloads. The approach thus provides for a “micro-service” enabling data analytic workloads to automatically and transparently use GPU resources without providing (e.g., to the data center customer) the underlying provisioning details. Preferably, the approach dynamically determines the number and the type of GPUs to use, and then during runtime auto-scales the GPUs based on workload.Type: GrantFiled: April 8, 2016Date of Patent: March 13, 2018Assignee: International Business Machines CorporationInventors: Min Li, John Alan Bivens, Koushik K. Das, Ruchi Mahindru, Harigovind V. Ramasamy, Yaoping Ruan, Valentina Salapura, Eugen Schenfeld