Min R Li

20200174899, Jun 4, 2020

Nov 29, 2018

16/204602

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Valentina SALAPURA - Chappaqua NY, US
John A. BIVENS - Ossining NY, US
Min LI - San Jose CA, US
Ruchi MAHINDRU - Elmsford NY, US
Yaoping RUAN - White Plains NY, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 11/20
H04L 29/08
H04L 12/927
H04L 12/24

A new approach to resiliency management is provided in a data center wherein servers are constructed dynamically, on-demand and based on workload requirements and a tenant's resiliency requirements by allocating resources from these pools. In this approach, a set of functionally-equivalent “interchangeable compute units” (ICUs) are composed of resources from resource pools that have been extended to include not only different resource types (CPU, memory, accelerators), but also resources of different specifications (specs) and flavors. As a workload is being processed, the health or status of the resources are monitored. Upon a performance issue or failure event, a resiliency manager can swap out a current ICU and replace it with a functionally-equivalent ICU. Preferably, individual ICUs are hosted on one of: resources of a same type each with different specifications, and resources of a same type and specification and different flavors. The approach enables failure independence in a disaggregated environment.

20200174949, Jun 4, 2020

Nov 29, 2018

16/204661

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Valentina SALAPURA - Chappaqua NY, US
John A. BIVENS - Ossining NY, US
Yaoping RUAN - White Plains NY, US
Min LI - San Jose CA, US
Ashish KUNDU - Elmsford NY, US
Ruchi MAHINDRU - Elmsford NY, US
Richard H. BOIVIE - Monroe CT, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 12/14
H04L 9/30

Server resources in a data center are disaggregated into shared server resource pools, which include a pool of secure processors. Advantageously, servers are constructed dynamically, on-demand and based on a tenant's workload requirements, by allocating from these resource pools. According to this disclosure, secure processor modules for new servers are allocated to provide security for data-in-use (and data-at-rest) in a dynamic fashion so that virtual and non-virtual capacity can be adjusted in the disaggregate compute system without any downtime, e.g., based on workload security requirements and data sensitivity characteristics. The approach herein optimizes an overall utilization of an available secure processors resource pool in the disaggregated environment. The resulting disaggregate compute system that is configured according to the approach cryptographically-protects workload data whenever it is outside the CPU chip.

20190354413, Nov 21, 2019

May 17, 2018

15/982579

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Ruchi MAHINDRU - Elmsford NY, US
Min LI - San Jose CA, US
Valentina SALAPURA - Chappaqua NY, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

G06F 9/50

Embodiments for optimizing memory placement in a disaggregated computing environment. A new workload is assigned to a subset of a plurality of processors, the subset of processors assigned a subset of a plurality of memory devices. In some embodiments, a determination is made as to whether the new workload is categorized as a memory-dependent workload having a memory need which can be met primarily by the subset of the memory devices. If the new workload is categorized as a memory-dependent workload, a determination is then made as to whether the subset of the memory devices is meeting the memory need of the new workload. When the subset of the memory devices is not meeting the memory need of the new workload, a memory related action is taken.

20190356729, Nov 21, 2019

May 17, 2018

15/982586

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Valentina SALAPURA - Chappaqua NY, US
Ruchi MAHINDRU - Elmsford NY, US
Min LI - San Jose CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

H04L 29/08
H04L 12/24

Embodiments for optimizing dynamic resource allocations for storage-dependent workloads in a disaggregated computing environment. A new workload is assigned to a subset of a plurality of processors, the subset of processors assigned a subset of a plurality of memory devices associated with a plurality of storage devices. A determination is made that the new workload is categorized as a storage-dependent workload having a storage need which can be met primarily by a subset of the storage devices after having identified whether data requests associated with the new workload can be satisfied by the subset of memory devices. Pursuant to determining the new workload is the storage-dependent workload, a storage related action is proactively performed to increase efficiency of the new workload prior to commencement of a performance of the new workload.

20190356731, Nov 21, 2019

May 17, 2018

15/982604

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Valentina SALAPURA - Chappaqua NY, US
Ruchi MAHINDRU - Elmsford NY, US
Min LI - San Jose CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

H04L 29/08
H04L 12/24

Embodiments for optimizing dynamic resource allocations in a disaggregated computing environment. A data heat map associated with a data access pattern of data elements associated with a workload is constructed. A locality of the data elements associated with the workload within the disaggregated computing environment is determined using the data heat map. Particular resources within pools of resources are assigned to a dynamically constructed disaggregated system in real-time based upon the locality of the data elements in relation to other ones of the resources within the pools of resources such that the dynamically constructed disaggregated system executes the workload using an optimized set of the particular resources.

20190356732, Nov 21, 2019

May 17, 2018

15/982612

- Armonk NY, US
Eugen SCHENFELD - South Brunswick NJ, US
Valentina SALAPURA - Chappaqua NY, US
Ruchi MAHINDRU - Elmsford NY, US
Min LI - San Jose CA, US

INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY

H04L 29/08
H04L 12/24

Embodiments for optimizing dynamic resource allocations in a disaggregated computing environment. A new workload is assigned to a subset of a plurality of processors, the subset of processors assigned a subset of a plurality of cache devices. A determination is made that the new workload is categorized as a cache-dependent workload which would be executed more efficiently were additional data elements associated with the new workload to be held in the subset of cache devices, and pursuant to determining the new workload is the cache-dependent workload, a determination is made as to whether the subset of cache devices is meeting the memory need of the new workload. Responsive to determining the subset of cache devices is not meeting the memory need of the new workload, a cache related action is performed.