An executable application's architecture may be mapped by executing the executable application, inputting a series of request data sets into the executable application, receiving one or more responses from the executable application, and performing an evaluation based on the responses. One or more indications of an architectural component may be extracted from metadata associated with the one or more received responses and associated with a corresponding request data set of the series of request data sets. The one or more indications of an architectural component may be associated with processing by the executable application of the corresponding request data set of the series of request data sets. An architecture of the executable application may be determined based on the one or more indications of an architectural component.

Systems, devices, computer-implemented methods, and/or computer program products that facilitate dynamic control of ZZ interactions for quantum computing devices. In one example, a quantum device can comprise a biasing component that is operatively coupled to first and second qubits via respective first and second drive lines. The biasing component can facilitate dynamic control of ZZ interactions between the first and second qubits using continuous wave (CW) tones applied via the respective first and second drive lines.

A session can be predicted and created on a user's computing device to thereby allow the user to immediately resume productivity upon logging in. When a user accesses a set of applications from multiple computing devices and/or at different times or locations, telemetry information can be captured and processed to generate session predictions for the user. The session predictions can then be employed to automatically create sessions on the user's computing devices based on the user's location and the time of day.

Certain embodiments of the present disclosure provide techniques for dynamically and reliably scaling a data processing pipeline in a computing environment. The method generally includes receiving a definition of a data pipeline to be instantiated on a set of resources in a computing environment. The data pipeline is converted into a plurality of steps, each step being defined as one or more workers. The one or more workers are instantiated. Each worker generally includes a user process and a processing coordinator to coordinate termination of the user process. Communications are orchestrated between one or more data sources and the one or more workers. The one or more workers are terminated by invoking a termination coordination process exposed by the user process and the processing coordinator associated with each worker of the one or more workers.

Technologies for dynamic accelerator selection include a compute sled. The compute sled includes a network interface controller to communicate with a remote accelerator of an accelerator sled over a network, where the network interface controller includes a local accelerator and a compute engine. The compute engine is to obtain network telemetry data indicative of a level of bandwidth saturation of the network. The compute engine is also to determine whether to accelerate a function managed by the compute sled. The compute engine is further to determine, in response to a determination to accelerate the function, whether to offload the function to the remote accelerator of the accelerator sled based on the telemetry data. Also the compute engine is to assign, in response a determination not to offload the function to the remote accelerator, the function to the local accelerator of the network interface controller.

Methods and systems for selecting a set of fast computable functions to assess core properties of entities are disclosed. A method includes: receiving a request to select a set of fast computable functions to determine core properties of an entity; determining, for each of a plurality of fast computable function nodes in a directed graph, a set of core property nodes in the directed graph that are connected to the fast computable function node; adding, to a solution set, a fast computable function node that is connected to a highest number of core property nodes that are currently unconnected to nodes in the solution set; repeating the adding until each of the core property nodes is connected to at least one of the nodes in the solution set; and outputting the fast computable function nodes in the solution set in response to the request.

A computer-implemented method for integrating client portals of underlying data processing applications through a shared log record, including: storing one or more log records that are each shared by the process management application and the version control application; receiving instructions through a user interface that integrates, through the shared one or more log records, the process management client portal with the version control client portal; in response to the receiving of the instructions, executing the received instructions, the executing of the received instructions including: selecting, by the version control application, a particular version of the rule from the multiple versions of the rule stored in the system storage; and transitioning, by the process management application, the particular version of the rule from the first state of the plurality of states to the second, different state of the plurality of states.

Adaptable internet-of-things (IoT) computing systems and methods are disclosed for improved and flexible declarative control of streaming data, such as Big Data, in compute intense environments. A declarative scripting engine determines an input data stream based on a first declarative statement defining input data stream variable(s) of a declarative scripting language in declarative scripting module(s). The input data stream is bound to a stream controller and is ingested into computer memory. The declarative scripting engine generates a snapshot data stream based on a second declarative statement in the declarative scripting module(s), and is derived from the input data stream. A stream model is defined, where a listener entity comprising an event is triggered based on the input data stream or the snapshot data stream as ingested into the stream model.

The present disclosure relates to a dataflow optimization method for low-power operation of a multicore system, the dataflow optimization method including: a step (a) of creating an FSM including a plurality of system states in consideration of dynamic factors that trigger a transition in system states for original dataflow; and a step (b) of optimizing the original dataflow through optimization of the created FSM.

An information processing method for determining a pattern that indicates an arrangement order of the plurality of tasks from upstream to downstream of a stream is performed by a computer. The method includes acquiring a plurality of patterns to be candidates of an arrangement order of the plurality of tasks from upstream to downstream of the stream in a case of executing the plurality of tasks using a stream processing format; specifying, for each pattern of the plurality of acquired patterns, an amount of data to be reintroduced from one task of the plurality of tasks to another task located upstream side of the stream with respect to the one task; and determining the pattern from among the plurality of patterns based on the specified amount of data to be reintroduced for the each pattern.