Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Systems and methods for inter-cluster deployment of compute services using federated operator components are generally described. In some examples, a first request to deploy a compute service may be received by a federated operator component. In various examples, the federated operator component may send a second request to provision a first compute resource for the compute service to a first cluster of compute nodes. In various examples, the first cluster of compute nodes may be associated with a first hierarchical level of a computing network. In some examples, the federated operator component may send a third request to provision a second compute resource for the compute service to a second cluster of compute nodes. The second cluster of compute nodes may be associated with a second hierarchical level of the computing network that is different from the first hierarchical level.

Abstract: A method, computer program product, and computer system for dividing a physical Ethernet port is provided. The method may include dividing, by a computing device, a first physical Ethernet port of a plurality of physical Ethernet ports into a plurality of partitions. A first partition of the plurality of partitions for the first Ethernet port may be assigned to a N-virtual distributed switch. A second partition of the plurality of partitions for the first Ethernet port may be assigned with a plurality of functions. Ethernet packets may be switched between the plurality of functions in the second partition.

Abstract: A method for execution of a synchronous operation in an asynchronous operational environment includes receiving, by a processor, a first operation from program code executing within the asynchronous operational environment with the program code being run on an execution thread and a communication thread. The method also includes determining, by the processor, if the first operation is a synchronous operation. The method further includes that if the first operation is a synchronous operation, sending a request from the execution thread to the communication thread to perform the first operation and blocking execution of a subsequent operation until a response to the request from the communication thread for the first operation has been completed.

Abstract: A method comprises receiving from a distributed app (dApp), a shard creation transaction in a blockchain block of a blockchain, the block comprising multiple shards; collecting, with a join block in the blockchain, transactions, the join block adjacent the blockchain block; encapsulating the shard creation transaction; applying the block including the shard creation transaction to yield a new shard in the block; and broadcasting the block.

Abstract: A computer-implemented method according to one aspect includes determining and storing characteristics of a plurality of cloud vendors; dividing a workload into a plurality of logical stages; determining characteristics of each of the plurality of logical stages; and for each of the plurality of logical stages, assigning the logical stage to one of the plurality of cloud vendors, based on a comparison of the characteristics of the plurality of cloud vendors to the characteristics of the logical stage. Data migration between the cloud vendors is performed during an implementation of the workload to ensure data is located at necessary cloud vendors during the corresponding tasks of the workload.

Abstract: A method includes receiving, by a producer thread of a plurality of producer threads, an offer request associated with an item. The producer thread increases a sequence and determines (i) a chunk identifier of a memory chunk from a pool of memory chunks and (ii) a first slot position in the memory chunk to offer the item. The producer thread also writes the item into the memory chunk at the first slot position. Then, a first consumer thread of a plurality of consumer threads determines the first slot position of the item and consumes the item at the first slot position. A second consumer thread consumes another item at a second slot position in the memory chunk and recycles the memory chunk.

Abstract: A method and a device for operating instance resources are provided. The method includes receiving an operation request, acquiring an instance resource associated with the target resource according to an instance arranging property, executing the operation on the instance resource associated with the target resource, and transmitting an operation response. The operation request includes a type of an operation and a target resource.

Abstract: A system and method for use with a cloud computing environment, for determining a cloud score associated with a resource configuration, limits, or shape, for example that of a virtual machine or host provided within the environment. The described approach provides a set of infrastructure workloads, for use in assessing a cloud infrastructure and resources provided thereby, so that a full spectrum of aspects of the cloud infrastructure can be covered by workload testing. The workloads can be used to generate metrics associated with resource usage. The system can then consider one or more metrics that are associated with performance of a particular resource configuration or shape, for example that of a virtual machine or (e.g., bare metal) host hosted by a cloud provider, and determine a score that is indicative of the relative performance of that configuration or shape for a particular workload configuration.

Abstract: The system obtains a first acyclic graph including multiple nodes and edges connecting the multiple nodes. A process to create a weave of the first acyclic graph produces a matching weave when executed on the first acyclic graph by different computing devices. An addition of a node to the first acyclic graph produces a second acyclic graph. The addition of the node to the first acyclic graph changes the weave of the first acyclic graph. The system obtains a process to reach a global consensus among the multiple computing devices. The process indicates a criterion to satisfy prior to reaching the global consensus and determines whether the multiple computing devices in the network satisfy the criterion. Upon determining that the criterion is satisfied, the system adds a finalize node to the first acyclic graph to obtain a third acyclic graph. A weave of the third acyclic graph cannot change.

Abstract: Certain embodiments described herein are directed to methods and systems for adding one or more nodes to a first cluster including a first node in a computer system. A method performed by the first node comprises receiving a first request from a second node to join the first cluster. The method also comprises retrieving a first cluster configuration associated with the first cluster from a distributed database through a first database server (DBS) and creating a second cluster configuration using the first cluster configuration and information received from the second node as part of the request. The method further comprises populating a first one or more local trust stores of a first one or more processes executing on the first node with a second one or more security certificates of a second one or more processes executing on the second node. The method further comprises writing the second cluster configuration to the distributed database and returning the second cluster configuration to the second node.

Abstract: There is provided a method and apparatus for vectorized resource scheduling using multi-dimensional hierarchical arrays with a uniform data type. According to embodiments, the hierarchy of resources may be represented as a multi-dimensional array of a uniform data type in a scheduling context. This data structure is known as a tensor. In various embodiments, a tensor may be used to model each of resource usage, requested resources, resource capabilities, tenant resource usage, etc. There is provided tensor scheduling operations (e.g. tensor scheduling algorithms) to make use of this resource model. Some embodiments may exploit specialized hardware, such as GPUs and tensor-processing units, in order to accelerate the tensor scheduling operations.

Abstract: A load balancing method, apparatus and device for a parallel model training task, and a computer-readable storage medium, includes: acquiring data traffic and a theoretical computational amount of each network layer in a target model; determining a theoretical computing capability of each computing device, and obtaining an initial computational amount corresponding to each computing device according to the theoretical computing capability and the theoretical computational amount; performing a load balancing operation according to the initial computational amount by using multiple device critical layer position division rule, so as to obtain a plurality of initial balancing schemes; compiling statistics on time performance parameters corresponding to the initial balancing schemes, and determining an intermediate balancing scheme from the initial balancing schemes according to the time performance parameters; and adjusting the intermediate balancing scheme according to the data traffic, so as to obtain a final

Abstract: Techniques are described for efficiently distributing across multiple computing resources satisfiability modulo theories (SMT) queries expressed in propositional logic with string variables. As part of the computing-related services provided by a cloud provider network, many cloud providers also offer identity and access management services, which generally help users to control access and permissions to the services and resources (e.g., compute instances, storage resources, etc.) obtained by users via a cloud provider network. By using resource policies, for example, users can granularly control which identities are able to access specific resources associated with the users' accounts and how those identities can use the resources. The ability to efficiently distribute the analysis of SMT queries expressed in propositional logic with string variables among any number of separate computing resources (e.g., among separate processes, compute instances, containers, etc.

Abstract: Examples are disclosed that relate to a disaggregated memory pool. One example provides a memory system comprising a memory controller and memory attached to the memory controller and forming at least a portion of a disaggregated memory pool, the disaggregated memory pool including a plurality of slices that are each dynamically assigned to a respective compute node. The memory system is configured to receive a request to adjust an assignment of the memory pool to a requesting compute node, where the portion of the memory pool includes an unassigned slice that can satisfy the request, assign at least part of the unassigned portion to the requesting compute node, and where the portion of the memory pool does not include an unassigned slice that can satisfy the request, cause a request to be directed to another compute node to free at least one slice to the such compute node.

Abstract: A non-contact method of characterizing the isostatic strength of a ceramic member or article includes capturing a digital image of the ceramic article, and then forming a two-dimensional representation of the ceramic article and the web therein based on the captured digital image. The method also includes performing finite-element analysis on the two-dimensional representation of the ceramic article using a select amount of simulated isostatic pressure to determine a maximum stress value within the two-dimensional representation of the web. The method further includes using the maximum stress value to characterize the isostatic strength of the ceramic article.

Abstract: A computing device receives a target value for a design quality metric. The target value indicates a desired quality of a design of an experiment and is related to an input parameter by a response curve. The computing device also validates the target value as being in a feasibility range for the design quality metric, and if so, determines a candidate value for the input parameter that yields a calculated value for the design quality metric. To determine the calculated value, the computing device iteratively adjusts the candidate value until the calculated value is within a predetermined tolerance of the target value. The computing device then updates an interactive graph visually representing the calculated value for the design quality metric as a function of the candidate value for the input parameter and outputs a graph visually representing the relationship that exists between the candidate value and the calculated value.

Abstract: A process and device for assigning a digital-assistant task to a mobile computing device in response to an incident. A mobile computing device determines digital-assistant tasks to be executed in response to the incident. Further the mobile computing device transmits a request for digital-assistant capability information to other mobile computing devices implementing respective digital assistants. Based on the digital-assistant capability received from one or more of the other mobile computing devices, the mobile computing device maps at least one of the digital-assistant tasks to the one or more of the other mobile computing devices. The mobile computing device assigns the at least one of the digital-assistant tasks to the mapped one or more of the other mobile computing devices and further transmits an instruction to execute the assigned digital-assistant tasks to the mapped one or more of the other mobile computing devices.

Abstract: A digital environment includes multiple computing nodes and a scheduling system that assigns workloads to computing nodes. The scheduling system includes an equivalence-class-based resource usage prediction system that receives a workload request and predicts an equivalence class for that workload request based on resource usage over time by the workload request or metadata associated with the workload request. The scheduling system also includes a workload assignment system that assigns the workload request to one or more of the computing nodes based on the predicted equivalence class. The number of equivalence classes is small relative to the total number of workloads that are scheduled (as an example, 10 to 15 equivalence classes for a total number of workloads in the tens or hundreds of thousands).

Abstract: In a computer-implemented method for allocating a host of a pre-configured hyper-converged computing device to a workload domain, a pre-configured hyper-converged computing device including a plurality of hosts is managed, wherein the plurality of hosts is allocable to workload domains. A pool of unallocated hosts of the plurality of hosts is managed within the pre-configured hyper-converged computing device, wherein hosts of the pool of unallocated hosts have associated hypervisor versions. An allocation request to allocate at least one host of the pool of unallocated hosts to a workload domain is received, the allocation request including a requested hypervisor version of at least one host upon allocation. The at least one host is updated to the requested hypervisor version of the allocation request while the at least one host is in the pool of unallocated hosts.