Abstract: A method for optimization of low-level memory operations in a distributed memory storage configuration that includes receiving, at a first processor, a request to migrate data from the first processor to a second processor, where the first processor and the second processor comprise a processor and memory, and identifying a command instruction associated with the requested data. The method also includes comparing a first performance metric associated with the first processor to a second performance metric associated with the second processor, where the first performance metric and the second performance metric are associated with executing the command instruction, and where, based on the comparing, a decision to move the command instruction to the second processor is formed, and migrating, responsive to the decision, the data and the command instruction to the second processor.

Abstract: Particular embodiments described herein provide for an electronic device that can be configured to receive a plurality of thermal parameters for a device, identify one or more of the plurality of thermal parameters that affect a thermal response of the device, and create a thermal vector for the device using the one or more of the plurality of thermal parameters that affect the thermal response of the device, where the thermal vector can be used to predict a new thermal response of the device. In an example, the thermal vector includes weighted thermal parameters.

Abstract: A determination is made of values for measures that affect processing of data in a computing environment comprising a client communicatively coupled to a server, wherein the measures include data factors, client factors, and server factors. A determination is made as to whether a load on the client is greater than the load on the server by calculating a load on the client and a load on the server based on the data factors, the client factors and the server factors, and then comparing the load on the client to the load on the server. In response to determining that the load on the client is greater than the load on the server, the data is stored at a location in the server, and an indication is made in a data structure in the client of a pointer to the location in the server.

Abstract: Methods and systems are described for balancing loads in distributed computer networks for computer processing requests with variable rule sets and dynamic processing loads. The methods and systems may include determining an initial allocation of the plurality of processing requests to the plurality of available domains that has a lowest initial sum excess processing load. The methods and systems may then retrieve an updated estimated processing load for at least one of the plurality of processing requests and determine a secondary allocation of the plurality of processing requests to the plurality of available domains.

Abstract: Various examples are disclosed for generating heatmaps and plotting utilization of hosts in a datacenter environment. A collector virtual machine can rove the datacenter and collect utilization data. The utilization data can be plotted on a heatmap to illustrate utilization hotspots in the datacenter environment.

Abstract: A workload manager uses on-band and off-band metrics to select a host server in a cluster to handle a connection request. The on-band metrics include CPU usage, memory usage, and vulnerability metrics. The off-band metrics include hardware component error logs. Utilization and vulnerability scores are calculated for each host server from the on-band metrics. A reliability score is calculated for each host server from the off-band metrics. A health score for each host server is calculated from the vulnerability and reliability scores. The health score is used to exclude unhealthy host servers from consideration. A priority score is calculated for each host server from the utilization, vulnerability, and reliability scores. The host server that has not been excluded and has the greatest priority score is selected to handle the connection request.

Abstract: Systems, apparatuses, methods, and computer programs for overprovisioning resources are disclosed. Resource usage statistics may be gathered for a plurality of client virtual machines (“VMs”). Statistical characteristics of resource usage by the plurality of client VMs may be calculated. It may also be determined which of the plurality of client VMs requesting resources to allocate resources to, as well as an amount of the resources to allocate, in a given time slot based on the calculated statistical characteristics.

Abstract: An information processing apparatus includes: a processor configured to: identify first data based on a history of accessing data in a past; obtain first load information from other apparatuses at a first time interval; identify second data based on the first load information and second load information of the information processing apparatus, the second data being stored in a memory; obtain third load information from a first apparatus that holds the first data and one or more second apparatuses that hold respective pieces of the second data at a second time interval shorter than the first time interval; and determine, when the first data is accessed, whether the first data is to be stored in the memory and which piece of the second data is to be deleted when temporarily storing the first data in the memory, based on the third load information and the second load information.

Abstract: A method includes: receiving, by a computer device, resource request for a data integration job, wherein the resource request is received from a job executor module and defines processes of the data integration job; allocating, by the computer device, containers for the processes of the data integration job; launching, by the computer device, a respective wrapper script on each respective one of the containers after allocating the respective one of the containers; and transmitting, by the computer device and in response to the allocating, node details to the job executor module. In embodiments, the wrapper script running on the container is configured to repeatedly check a predefined location for process commands from a job executor. After the resource manager allocates all the containers for a data integration job according to a resource request, the job executor writes the process commands to the predefined location.

Abstract: The machine implemented method for operating at least one electronic system comprises detecting a pattern of use of plural control parameters in a path through a graph of operational context switches to reach a target operational context; storing a representation of the pattern in association with an indicator identifying the target operational context; responsive to detecting at least one of a request for a switch of operation from a source operational context to the target operational context, a trapping on a resource access, and a detection of a breakpoint, retrieving the representation in accordance with the indicator identifying the target operational context; and responsive to the retrieving, applying at least one control parameter to said at least one electronic system to match the pattern.

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for determining an accurate and efficient auto-scaling action for a cloud-based computing cluster based on multiple proposed auto-scaling actions from multiple scaling models. For example, the disclosed systems can determine an auto-scaling action to perform on a cloud-based computing cluster by weighing multiple proposed auto-scaling actions from multiple scaling models based on confidence scores associated with the proposed auto-scaling actions. Moreover, the disclosed systems can modify the cloud-based computing cluster using the determined auto-scaling action (e.g., to accurately and efficiently provision computing resources for a cloud-based computing system).

Abstract: Managing execution of a job in a computing environment. A method establishes, for a job to be executed in the computing environment, an execution plan for processing the job. The execution plan identifies computationally intensive tasks of the job and data intensive tasks of the job. The method selects a virtual machine of the computing environment to process the identified computationally intensive tasks of the job and identified data intensive tasks of the job. The method assigns the identified computationally intensive tasks of the job for foreground processing of the virtual machine and assigns the identified data intensive tasks of the job for background processing of the virtual machine. Execution of the job executes the identified computationally intensive tasks of the job in foreground processing of the virtual machine and executes the identified data intensive tasks of the job in background processing of the virtual machine.

Abstract: In a data processing system running at least one application on a hardware platform that includes at least one processor and a plurality of coprocessors, at least one kernel dispatched by an application is intercepted by an intermediate software layer running logically between the application and the system software. Compute functions are determined within kernel(s), and data dependencies are determined among the compute functions. The compute functions are dispatched to selected ones of the coprocessors based at least in part on the determined data dependencies and kernel results are returned to the application that dispatched the respective kernel.

Abstract: A system, apparatus, and method for thread synchronization is provided. In one embodiment, a network system receives a signal from a first computing machine, and determines whether one or more processes are waiting for the signal. The network system also transmits the signal to one of the one or more processes on the first computing machine or a second computing machine to execute a thread of the process.

Abstract: A system for scheduling and dispatching workload items between tasks can include an aggregated file structure and a task scheduler. The aggregated file structure comprises at least one logical partition with each partition having a secondary operating system and address spaces and a plurality of tasks executable therein. The task scheduler is executable from the primary operating system and can receive a service request from a task requesting an action from at least one other task and writing the action, a first task identifier, and at least one other task identifier to at least one private memory address associated with the other task or tasks. The service request action can be a start service request, a stop service request, a suspend service request, a resume service request, change the order of execution service request, or a change priority of executing tasks service request.

Abstract: Migration from legacy infrastructure (e.g., hypervisor-based virtualization systems utilizing virtual machines (VMs)) to container-based virtualization systems utilizing containers is simplified and accelerated via automation. By utilizing capabilities provided by the Internet Standards Organization (ISO) Open Systems Interconnection model (OSI model) for system standardization, system, application, and data components of VMs can be migrated to containers.

Abstract: Provided are a computer program product, network computing system, and method for automated system integration. A first system gathers a request list of requested computational resources to transmit to the second system, receives a list of accessible computational resources available through the second system, and determines matching computational resources in the request list that match computational resources in the list of accessible computational resources. The first system sends information on the matching computational resources to the second system. The second system gathers the matching computational resources received from the first system to make accessible to the first system at a resource location accessible over a network and sends access information for the matching computational resources gathered by the second system.

Abstract: In one embodiment, a method for improved management of virtual machine clusters may include: determining a current utilization value for each of a plurality of virtual machines (VMs) in a cluster, the VMs associated with a plurality of applications; storing the current utilization values for each of the plurality of VMs in a utilization table; determining that a capacity threshold for the cluster has not been reached based on an aggregation of the current utilization values for the plurality of VMs; provisioning a new VM into the cluster; storing a default utilization value for the new VM in the utilization table; and re-determining the capacity threshold based on the aggregated stored current utilization values for the plurality of VMs and the stored default utilization value for the new VM until a maturity threshold for the new VM is reached.

Abstract: Techniques for use in a microprocessor core for soft watermarking in thread shared resources implemented through thread mediation. A thread is removed from a thread mediation decision involving multiple threads competing or requesting to use a shared resource at a current clock cycle based on a number of entries in the shared resource that the thread is estimated to have allocated to it at the current clock cycle. By removing the thread from the thread mediation decision, the thread is stalled from allocating additional entries in the shared resource.

Abstract: A computing system includes: a command fetch block configured to determine a host profile for representing a requesting host corresponding to a processing request; and a credit checker block, coupled to the command fetch block, configured to calculate an instance budget at a communication endpoint from an overall resource of the communication endpoint for controlling the processing request at the communication endpoint.