A method for using a user-fillable form in a host container includes receiving, at a host container, a user-fillable form bound to dynamic data from an underlying data source where the user-fillable form has a data structure generated by prepopulated coding. The method further includes translating the user-fillable form into a hostable format for the host container. The method also includes rendering, using the hostable format for the host container, the user-fillable form in a user interface. The method further includes receiving, at the user interface of the host container, from a user of the host container, a data entry for input to the user-fillable form and updating, by the host container, the dynamic data from the underlying data source by persisting data from the data entry in a data store associated with the underlying data source.

An illustrative method includes receiving a write request to write payload data to a virtual storage volume; transmitting the write request to a plurality of storage nodes each storing a replica of the virtual storage volume; acknowledging the write request only after a quorum of the storage nodes has stored the payload in their respective kernel memory; and flushing the payloads stored in each kernel memory to persistent storage only after a threshold number of outstanding write requests that have been acknowledged, but not yet flushed, has been reached, the flushing configured to optimize performance for synchronous workloads.

Operation of a non-volatile memory (NVM) storage module may comprise receiving a plurality of commands as associated with a plurality of priority-based queues from a host-memory. A received command is evaluated in accordance with a priority associated with the queue storing the command and a size of the command. The evaluated command is split into a plurality of sub-commands, each of the sub-commands having a size determined in accordance with the evaluation. A predetermined number of hardware resources are allocated for each of the evaluated command based on at least the size of each of the sub-commands to thereby enable a processing of the evaluated command based on the allocated resources. Quality of service (QoS) for the evaluated-command may thus be augmented.

The disclosed system implements techniques to secure communications for injecting a workload (e.g., a container) into a virtual network hosted by a cloud-based platform. Based on a delegation instruction received from a tenant, a virtual network of the tenant can connect to and execute a workload via a virtual machine that is part of a virtual network that belongs to a resource provider. To secure calls and authorize access to the tenant's virtual network, authentication information provided with a call from the virtual network of the resource provider may need to match authorization information made available via a publication service of the cloud-based platform. Additionally or alternatively, an identifier of a NIC used to make a call may need to correspond to a registered name of the resource provider for the call to be authorized. These checks provide increased security by preventing unauthorized calls to the tenant's virtual network.

Techniques in advanced deep learning provide improvements in one or more of accuracy, performance, and energy efficiency, such as accuracy of learning, accuracy of prediction, speed of learning, performance of learning, and energy efficiency of learning. An array of processing elements performs flow-based computations on wavelets of data. Each processing element has a respective compute element and a respective routing element. Each compute element has processing resources and memory resources. Each router enables communication via wavelets with at least nearest neighbors in a 2D mesh. Stochastic gradient descent, mini-batch gradient descent, and continuous propagation gradient descent are techniques usable to train weights of a neural network modeled by the processing elements. Reverse checkpoint is usable to reduce memory usage during the training.

A method is provided for determining command-to-process correspondence. The method includes identifying, by the hardware processor, initial processes resulting from executions of container immutability change events for each of multiple containers in a cluster, based on an execution time, a process identifier and a process group identifier for each of the container immutability change events. The method further includes checking, by the hardware processor, if an initial process from among the identified initial processes matches an entry in a database that stores external container commands and at least one respective process resulting from executing each of the external container commands. The method also includes designating, by the hardware processor, a particular external command, from among the external container commands stored in the database, as having a correspondence to the initial process, responsive to the initial process matching the at least one respective process resulting from executing the particular external command.

Embodiments of the present application provide an acceleration management node. The acceleration management node separately receives acceleration device information of all acceleration devices. The acceleration device information includes an algorithm type, an acceleration bandwidth or non-uniform memory access architecture (NUMA). The acceleration management node obtains an invocation request from a client. The acceleration management node queries the acceleration device information to determine, from all the acceleration devices of the at least one acceleration node, a target acceleration device matching the invocation request. The acceleration management node further instructs a target acceleration node to respond to the invocation request.

Techniques for optimizing CPU usage in a host system based on VM guest OS power and performance management are provided. In one embodiment, a hypervisor of the host system can capture information from a VM guest OS that pertains to a target power or performance state set by the guest OS for a vCPU of the VM. The hypervisor can then perform, based on the captured information, one or more actions that align usage of host CPU resources by the vCPU with the target power or performance state.

According to examples, an apparatus may include a memory on which is stored machine-readable instructions that may cause a processor to determine, for each of a plurality of members in a group, a respective least privilege level for a resource and determine, based on the determined respective least privilege levels, a privilege level to be assigned to the group for the resource. The instructions may also cause the processor to assign the determined privilege level to the group for the resource and apply the assigned privilege level to the members of the group for the resource.

A software switch and a method performed by the software switch are disclosed. The software switch receives, from a node deploying a virtual machine, a request for a virtual port to be polled by the virtual machine. The request includes a Central Processing Unit “CPU” identity identifying a CPU on which the virtual machine executes. The request includes an indication of a clock frequency at which the CPU is set to operate. The software switch determines a number of packets in a queue associated with the virtual port. The software switch adjusts the clock frequency of the CPU based on the number of packets in the queue. A corresponding computer program and a computer program carrier are also disclosed.