International Business Machines Corporation

Wentech Solutions Inc.

Kenneth Blair Kent

Michael H Dawson

Aleksandar Micic

Peter Duncan Shipton

Daniel J Heidinga

Angela Lin

Oluwatobi Ajila

Panagiotis Patros

Eric Aubanel

Bing Yang

Devarghya Bhattacharya

Joran S C Siu

Konstantin Nasartschuk

Amir Allaf-Akbari

Kevin John Shiell

Farough Motasemi

Panos Patros

Taees Eimouri

Sujit Bhandari

Maria Patrou

Dayal D Dilli

Systems and methods are described for performing at least one of assessing, optimizing and/or controlling the performance of an Anaerobic Digestion (AD) plant. The system comprises a server that provides a user interface for allowing a user to enter user inputs to define various aspects of the AD plant operation and to view results of the simulation; a database for storing the inputs used for the simulation of the anaerobic digestion plant, the inputs including feedstock inputs, AD operational inputs, and simulation criteria; and a simulation engine that can be operated in an at least one of an off-line simulation mode for generating off-line simulator predictions, a near-line simulation mode for optimizing the performance of the system and an online mode for using machine learning to tune the performance of various models used in simulating the operation of the AD plant.

System and method for anaerobic digestion process assessment, optimization and/or control

A method manages a cluster. A computer system determines a measurement of a process variable for the cluster, wherein the process variable indicates a quality of service for the cluster. The computer system determines a comparison between the measurement of the process variable and a desired value for the process variable. The computer system determines an adjustment to a setpoint for a runtime metric in the cluster based on the comparison, wherein the runtime metric is a control variable for the cluster. The computer system updates the setpoint for the runtime metric in a controller for the cluster using the adjustment, wherein the runtime metric is used by the controller as the control variable to scale a set of resources in the cluster to cause a value of the runtime metric to move towards the setpoint.

Automatic cluster scaling based on varying workloads

Aspects of the present invention provide devices that determine a load for each tenant of a plurality of tenants running applications on a shared computer server for a predetermined interval of time, wherein the computer server includes a plurality of computer processor cores, compute a capacity for each tenant of the plurality of tenants which includes a difference between the load and a service level agreement for each tenant, determine computer processor cores corresponding to the capacity of a largest capacity tenant, wherein the processors cores include a subset of the plurality of computer processor cores for the shared computer server, pin the subset of computer processor cores to perform garbage collection for one or more tenants, and invoke the garbage collection using the pinned subset of computer processor cores which deallocates no longer used memory in a corresponding heap for the one or more tenants.

Multi-tenant cloud elastic garbage collector

Objects are managed in a virtual machine. A frequency of access to fields in objects for an application is identified while the application runs in the virtual machine. An object in the objects is split into a hot object and a cold semi-object based on the frequency of access to the fields in the object as identified while the application runs in the virtual machine, wherein cache misses are reduced from splitting objects based of the frequency of access.

Fields hotness based object splitting

Aspects provide multi-tier data synchronization based on a concurrent linked monitor list. A computer processor associates each of different data regions of a packed data object with different mutual exclusion monitor nodes of a linked list, the data regions defined by a data offset location within memory data and a length of the data region from the offset. In response to determining that a first data region of the packed data object is on-heap memory, the processor associates the first data region with a container representative of the linked list sorted in ascending order of the respective offset values, and a hash code of the container; and in response to determining that a second data region of the packed data object is off-heap memory, stores container information for the second data region in the linked list and resorts the linked-list nodes of container information in ascending order of offset values.

Multi-tier data synchronizer based on concurrent linked list

A first execution of an application is performed on a virtual machine. A set of virtual machine parameters associated with the first execution is determined. One or more command lines of the application are mapped to the set of virtual machine parameters. The mapping is stored in a cache. A second execution of the application is performed on the virtual machine. The second execution retrieves the set of virtual machine parameters from the cache.

Enhancing virtual machine performance using autonomics

Embodiments disclose systems, methods and computer program products to perform an operation for sharing artifacts between instances of an application deployed in a cloud computing environment. The operation generally includes upon determining, during staging of the application, that a set of artifacts are not available for instances of the application to share in the cloud computing environment, generating the set of artifacts via a first application instance, storing the set of artifacts, and requesting a re-staging of the application. The operation also includes during the re-staging of the application, generating a file for deploying scaled instances of the application and packing the stored set of artifacts into the generated file via a second application instance. The operation further includes executing an instance scale out of the application with the generated file comprising the stored set of artifacts.

Dynamically compiled artifact sharing on PaaS clouds

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Fredericton, Canada

Kenneth Blair Kent