A multitenant infrastructure server (MTIS) is configured to provide an environment to execute a computer routine of an arbitrary application. The MTIS receives a request from a webtask server to execute the computer routine in a webtask container. The computer routine is executed in the webtask container at the MTIS. Upon successful execution of the computer routine, a result set is returned to the webtask server. If the execution of the computer routine is unsuccessful, an error notification is returned to the webtask server. The resources consumed during the execution of the computer routine are determined. The webtask container is destroyed to prevent persistent storage of the computer routine on the MTIS.

Rules can be generated for migrating dependencies of a software application. For example, a computing device can receive a source version of a dependency of a software application and a target version of the dependency of the software application. The computing device can compare the source version to the target version to determine a difference between the source version and the target version. The computing device can receive a template for a rule indicating a location in the source version to be modified for the software application to support the target version. The template can include a fillable section. The computing device can populate the fillable section of the template with a value based on the difference between the source version and the target version.

According to some embodiments, methods and systems may be associated with a cloud computing environment having an integration service (e.g., associated with a Software-as-a-Service or a Platform-as-a-Service). A design micro service may have a User Interface (“UI”) framework and UI components in a domain specific language for an integration developer. A custom flow step development kit may receive, from the integration developer via a browser-based graphical UI, information to build logic for a custom flow step associated with a microservice-based integration service. In some embodiments, a new integration component is embedded into an existing set of components for a tenant, and the new custom flow step is deployed in, and re-usable by, other integration services (e.g., via a marketplace).

Provided is an automatic event graph construction method for multi-source vulnerability information. The method includes the following steps. A vulnerability report is crawled from a vulnerability database, a cause of vulnerability is taken as an event trigger word, and a vulnerability type is determined through the cause of vulnerability. An attacker, consequence, location and other information in a description are identified by named-entity recognition, and information completion is performed. An explicit relation between events is extracted by using text information, an implicit relation between events is extracted by using text similarity, and vulnerability-related code representation is performed. Obtained vulnerability event information is visualized into an event graph through a visualization tool.

Code translation is an evolving field and due to advancements in the infrastructure and compute power. The existing methods for code translation are time and effort intensive. A method and system for translation of codes based on the semantic similarity have been provided. A machine learning model is developed, that understands and encapsulates the semantics of the code in the source side and translates the semantic equivalent code which is more maintainable and efficient compared to one to one translation. The system is configured to group a plurality of statements present in the source code together into blocks of code and comprehend the semantics of the block. The system is also trained to understand syntactically different but semantically similar statements. While understanding the semantics of the block and translating, the unused/duplicate code etc. gets eliminated. The translated code is better architected and native to the target environment.

A compiler for a gate-based superconducting quantum computer compiles hybrid classical/quantum algorithms for quantum processing cells with different configurations. The compiler inputs the algorithm and outputs code in a target language executable by a quantum processing cell of a quantum processing system that can execute the algorithm. The compiler includes various functionality, such as: parsing, analyzing control flows, addressing, compressing, and translating. The compiler optimizes algorithms in various manners using the functionality. Some optimizations include addressing efficiently, compressing based on simulations, and translating for efficient execution of parametric functions. The compiler may function in the environment of a cloud quantum computing system. The cloud quantum computing system may receive algorithms from remote access nodes for execution on local classical and quantum computing systems.

Some embodiments provide a compiler for optimizing the implementation of a machine-trained network (e.g., a neural network) on an integrated circuit (IC). The compiler of some embodiments receives a specification of a machine-trained network including multiple layers of computation nodes and generates a graph representing options for implementing the machine-trained network in the IC. In some embodiments, the graph includes nodes representing options for implementing each layer of the machine-trained network and edges between nodes for different layers representing different implementations that are compatible. The compiler of some embodiments is also responsible for generating instructions relating to shutting down (and waking up) memory units of cores. In some embodiments, the memory units to shutdown are determined by the compiler based on the data that is stored or will be stored in the particular memory units.

This disclosure describes techniques implemented partly by a service provider network for containerizing applications. In an example, the techniques may include requesting process relationship information for one or more potential processes of an application, receiving the requested process relationship information for the one or more potential processes of the application, and based on the received process relationship information, configuring a process relationship detection algorithm. Then, using the configured process relationship detection algorithm, the techniques may determine a respective relationship score for individual process pairs of processes operating on a system executing the application and determine one or more individual process pairs that have a respective relationship score that is equal to or above a threshold to be one or more cooperating process pairs.

Systems and methods analyze for installing dependencies required for the installation of prerequisite components of cloud infrastructure to be installed in a disconnected environment are presented herein. An automation playbook generated after an assessment of a disconnected environment may be analyzed to determine a set of dependencies required by the automation playbook (e.g., packages and files required by each installation playbook called by the automation playbook). Each of the dependencies may be brought into the disconnected environment and installed as operating system packaging units, or deployed as containerized services. After all of the dependencies have been installed, a processing device may generate an installation report indicating whether the installation of each prerequisite component was successful or not. Upon determining that each of the prerequisite components was successfully installed, the processing device may install the cloud infrastructure on the disconnected environment.

Apparatuses, systems, and techniques to combine operations. In at least one embodiment, a processor causes two or more dependent reduction operations to be combined into a software kernel.