Abstract: A system is disclosed. The system includes a resource monitor to monitor a resource utilization of a set of resources of one or more instances, the resource utilization corresponding to a first level of performance and cost and an instance type determiner to, based on the resource utilization, determine if there is an instance type for at least one of the one or more instances, with a resource profile, that will provide a second level of performance and cost that is closer to a default level of performance and cost than the first level of performance and cost. In addition, the system also includes an instance type recommender to, based on the determining, perform one of making and not making a recommendation to replace the instance type of the at least one of the one or more instances.

Abstract: Technologies for composing a managed node with multiple processors on multiple compute sleds to cooperatively execute a workload include a memory, one or more processors connected to the memory, and an accelerator. The accelerator further includes a coherence logic unit that is configured to receive a node configuration request to execute a workload. The node configuration request identifies the compute sled and a second compute sled to be included in a managed node. The coherence logic unit is further configured to modify a portion of local working data associated with the workload on the compute sled in the memory with the one or more processors of the compute sled, determine coherence data indicative of the modification made by the one or more processors of the compute sled to the local working data in the memory, and send the coherence data to the second compute sled of the managed node.

Abstract: A system is disclosed. The system includes a resource monitor to monitor a resource utilization of a set of resources of one or more instances, the resource utilization corresponding to a first level of performance and cost and an instance type determiner to, based on the resource utilization, determine if there is an instance type for at least one of the one or more instances, with a resource profile, that will provide a second level of performance and cost that is closer to a default level of performance and cost than the first level of performance and cost. In addition, the system also includes an instance type recommender to, based on the determining, perform one of making and not making a recommendation to replace the instance type of the at least one of the one or more instances.

Abstract: An apparatus and method for conditional quality of service in a processor. For example, one embodiment of a processor comprises: a plurality of processor resources to be allocated to a plurality of executed processes in accordance with a set of quality of service (QoS) rules; and conditional quality of service (QoS) circuitry/logic to monitor usage of the plurality of processor resources by the plurality of processes and to responsively modify an allocation of a first processor resource for a first process in response to detecting a first threshold value being reached in a second resource allocated to the first process.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: Techniques for predictive autoscaling and resource optimization of software deployments. In an implementation, users declare performance objectives, and machine learning of application behavior and load profile is to used to determine minimum cost resourcing to meet the declared performance objectives. In an embodiment, convergent deployments are monitored and related feedback is provided to improve forecasting, behavior modeling, and resource estimation over time.

Abstract: A system can receive information about a first orchestration service that indicates a mapping from an application programming interface (API) to an executable script, and a dependency of the first orchestration service on a second orchestration service. The system can, in response to receiving the information, creating a base container image for the first orchestration service. The system can associate the API with executing the executable script on the base container image. The system can associate the dependency of the first orchestration service on the second orchestration service with the base container image. The system can, in response to receiving data indicative of a request to create an instance of the first orchestration service, creating an instance of the base container image.

Abstract: Allowing an execution of an allocation processing and allocation release the processing of a device to a service program during an execution of the service program. Under control of an execution management section (1112), in case device transmission data received is device transmission data satisfying a predetermined transition condition of a state transition, a service state of the service program is updated. Then, under control of an execution management section (1112), a notification of the service state update is transmitted to a service context determination section (113). Under control of the service context determination section (113), whether there is a change in a service context to be executed on the service program based on service context information is confirmed.

Abstract: A processing system concurrency optimization system includes a processing system having first and second processing subsystems, a power system that is coupled to the first and second processing subsystems, a processing system concurrency optimization database, and a processing system concurrency optimization subsystem that is coupled to the power system and the processing system concurrency optimization database. The processing system concurrency optimization subsystem determines that a first workload has been provided for performance by the processing system, and identifies a first processing system concurrency optimization profile that is associated with the first workload in the processing system concurrency optimization database.

Abstract: A method, system and apparatus for the sharing of an FPGA board by multiple virtual machines. Specifically, in the present application, a PCIE virtual layer (comprising a plurality of PCIE virtual sub-layers) and a virtual PCIE device are created; one virtual machine corresponds to one virtual PCIE device, multiple virtual PCIE devices correspond to one PCIE virtual sub-layer, and one PCIE virtual sub-layer corresponds to one FPGA board, thus enabling multiple virtual machines to share and use the FPGA board through one PCIE virtual sub-layer (that is, the multiple virtual machines share one PCIE bus, and same all access the FPGA board through the PCIE bus), thereby solving the problem of some of the virtual machines being unable to be started at the same time, and enhancing the experience effect of a user.

Abstract: A virtual network comprising virtual machines executing at a computing environment remote from the virtualized computing service provider is implemented. A control plane management functions is configured to provide and implement the virtual machines of the virtual network and executed at the virtualized computing service provider. Data plane management functions are configured to manage data traffic to and from the virtual machines of the virtual network and executed at the remote computing environment. A secure network connection between the virtualized computing service provider and the remote computing environment is established. The control plane management functions cause instantiation of the virtual machines of the virtual network at the remote computing environment. Using the control plane management functions executing at the virtualized computing service provider, operation of the virtual machines of the virtual network is managed.

Abstract: Some embodiments provide a novel method for collecting and reporting attributes of data flows associated with machines executing on a plurality of host computers to an analysis appliance. Some embodiments collect, each time a request for a new data message flow is initiated, a set of contextual attributes (i.e., context data) associated with the requested new data message flow. The method, in some embodiments, generates a correlation data set and provides the correlation data set to be included in flow data regarding the requested data message flow to be used by the analysis appliance to correlate context data and flow data received as separate data sets from multiple host computers.

Abstract: Various embodiments include a coordinator node for coordinating a multiparty computation (MPC) on one or more datasets. The system comprises a plurality of client nodes, one or more datasets and a plurality of computation nodes. Client nodes may include at least one dataset and/or at least one computation node that can operate as a party to an MPC. The coordinator node is configured to receive a request for an MPC on one or more of the datasets from a requesting node, the MPC including the evaluation of at least one function by two or more computation nodes from different client nodes; determine a computation schedule for the MPC, the computation schedule indicating which client nodes of the plurality of client nodes are to participate in the MPC; send at least part of the determined computation schedule to at least one of the client nodes indicated in the determined computation schedule.

Abstract: A method for combining multiple different data processing, artificial intelligence and/or machine learning frameworks for execution by a target hardware includes extracting one or more computation graphs from each of the different frameworks. The computation graphs are combined into a fused computation graph. Memcopy operations are removed at edges between the computation graphs of the different frameworks. Memory spaces for computations in the fused computation graph are remapped to memory spaces of the target hardware.

Abstract: A data processing device that can monitor properly the state of the interrupt processing of a virtual machine is provided. The data processing device according to an aspect of the present disclosure includes an arithmetic unit that executes multiple virtual machines, respectively, and an interrupt controller that instructs execution of the interrupt processing to the arithmetic unit with the virtual machine information to specify at least one of the multiple virtual machines. The interrupt controller includes a counter to count the number of interrupts for each virtual machine based on the virtual machine information.

Abstract: The present invention describes a system and a method for dynamically optimising the computing resources allocated to a client application in different data regions of one or more service providers. A number of monitoring modules are provided in each data regions, which are configured to collect operational information from each data region, which is communicated to the other data regions. As such, all data regions are aware of the operational environment of the other data regions.

Abstract: A cloud computing capacity management system can include a fine-grained admission control layer, a policy engine, and an enforcement layer. The fine-grained admission control layer can be configured to ingest capacity signals and create a capacity mitigation policy, based at least in part on the capacity signals, to protect available capacity of a cloud computing system for prioritized users. The capacity mitigation policy can be directed to users of the cloud computing system. The policy engine can be configured to control how the capacity mitigation policy is applied to the cloud computing system. The enforcement layer can be configured to handle incoming resource requests and to enforce resource limits based on the capacity mitigation policy as applied by the policy engine.

Abstract: Methods and systems for determining performance of a hosted application are described herein. Determining the performance of a hosted application may require the calculation of scores corresponding to metrics about user experience, including a user workload context, a user action, a frame rate, a round trip latency time, and image quality. The scores associated with the metrics about user experience may be weighted against each other, in accordance with an equation, described herein, to calculate a value corresponding to the performance of a hosted application. Data may be generated and shared with both a virtual computing environment and an administrator of the virtual computing environment. The data may include instructions to optimize user experience within the virtual computing environment. The instructions may be executed by the virtual computing environment to prepare the virtual computing environment for further user interaction.

Abstract: Virtualization exploits virtual rather than actual elements such as computer hardware platforms, storage devices, and computer network resources for example. However, prior art techniques have limitations including, for example, memory requirements and resource requirements which typically either limit their deployment to remote server based systems or limit the number of concurrent virtual machines a system can support. Embodiments of the invention address these limitations by supporting application virtualization on foreign operating systems with reduced resource usage by removing the requirement for virtualization of the entire foreign operating system. The inventive virtualization provides creation of an isolated memory space with isolated code execution using hardware assistance.

Abstract: A computer-implemented method to schedule special containers using a multi-queue scheduler. The method includes receiving, by a scheduler, a first pod including a first container including a first queue, a second queue, an event handler, and an error handler. The method further includes obtaining a set of characteristics for the first pod and determining that the first pod is a special pod. The method includes adding the first pod to the first queue, wherein the first queue is a special queue and includes a special function. The method also includes initiating the special function. The method further includes assigning, based on one or more placement rules, the first pod to a first node of a plurality of nodes.