A method includes receiving a high-level function in a high-level code of an application; identifying resources in a hardware to execute a set of low-level instructions that is generated from the high-level function in the high-level code; compiling the high-level function in the high-level code of the application into the set of low-level instructions to be executed on the hardware; and generating a plurality of structured metadata associated with allocation of resources in the hardware to execute the set of low-level instructions.

The present application is directed towards systems and methods for providing a heat map interface for analyzing and reporting transformation capabilities of a source installation to a target installation of an application. Characteristics of the source installation are displayed in an easy, intuitive interface, providing improved efficiency in analysis and planning. Furthermore, the interface is interactive, allowing an administrator or user to select and apply transformation dispositions to code objects grouped into regions and sub-regions, providing versatility and accuracy of configuration.

A method for implementing confidential machine learning with program compartmentalization includes implementing a development stage to design an ML program, including annotating source code of the ML program to generate an ML program annotation, performing program analysis based on the development stage, including compiling the source code of the ML program based on the ML program annotation, inserting binary code based on the program analysis, including inserting run-time code into a confidential part of the ML program and a non-confidential part of the ML program, and generating an ML model by executing the ML program with the inserted binary code to protect the confidentiality of the ML model and the ML program from attack.

The present specification provides a method for executing a smart contract, a blockchain node, and a storage medium. An implementation of a method for executing a smart contract includes: receiving, by a blockchain node, a request for creating a smart contract, the request including a bytecode of the smart contract; starting, by the blockchain node after completing deployment of the smart contract, to compile the bytecode of the smart contract into a first machine code by using ahead-of-time compilation and storing the machine code; and performing, by the blockchain node in execution of the deployed smart contract and in response to the first machine code of the smart contract not being locally stored, JIT compilation on the bytecode of the smart contract to obtain a second machine code and storing the second machine code, and executing the second machine code.

The disclosure describes various aspects of a software-defined quantum computer. For example, a software-defined quantum computing architecture for allocating qubits is described that includes an application programming interface (API); a quantum operating system (OS) on which the API executes, with the quantum OS including a resource manager and a switch; and a plurality of quantum cores connected by the switch of the quantum resource OS. Moreover, the resource manager of the quantum resource OS determines an allocation of a plurality of qubits in the plurality of quantum cores.

A system comprises at least one hardware processor and a memory storing instructions. When executed, the instructions cause the at least one hardware processor to perform operations comprising receiving, in a compiling process, a request to create a Java user-defined table function (Java UDTF), the Java UDTF including code related to receiving one or more input tables and transforming the one or more input tables to an output table; verifying a construct of the Java UDTF in the request is correct; and compiling to generate execution code that includes the Java UDTF when the construct of the Java UDTF is correct.

The disclosure describes various aspects of a software-defined quantum computer. For example, a software-defined quantum computer and an expandable/modular quantum computer are described. Also described are at least a software-defined quantum architecture, a resource manager workflow, a quantum compiler architecture, hardware description language configuration, levels of application programming interface (API) access points, and exception handling in software-defined quantum architecture.

A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: acquiring a plurality of regular expressions that is able to be used to search for a portion to be processed from each piece of data of a data group that is generated on the basis of the data included in the data group and data that indicates a processing example of the data; calculating a likelihood of using each regular expression to process the data group on the basis of a portion that corresponds to each of the plurality of acquired regular expressions in each piece of the data of the data group; and outputting the calculated likelihood of each of the regular expressions.

The present specification provides a method for executing a smart contract, a blockchain node, and a storage medium. An implementation of a method for executing a smart contract includes: receiving, by a blockchain node, a request for creating a smart contract, the request including a bytecode of the smart contract; starting, by the blockchain node after completing deployment of the smart contract, to compile the bytecode of the smart contract into a first machine code by using ahead-of-time compilation and storing the machine code; and performing, by the blockchain node in execution of the deployed smart contract and in response to the first machine code of the smart contract not being locally stored, JIT compilation on the bytecode of the smart contract to obtain a second machine code and storing the second machine code, and executing the second machine code. According to the above implementations of the present specification, when AoT compilation is not completed, JIT compilation execution is performed on the bytecode of the smart contract, so normal processing of a blockchain service request can be ensured while AoT compilation is performed.

Certain aspects of the present disclosure provide techniques for generating knowledge graphs from program source code. An example method generally includes receiving a source code definition of a workflow implemented in an application. The source code definition of the workflow is converted into an intermediate representation of the workflow, the intermediate representation comprising a condensed version of the source code definition. An abstract syntax tree representation of the workflow is generated based on the intermediate representation of the workflow. A structured file is generated by traversing the abstract syntax tree representation of the workflow, wherein the structured file comprises a definition of the workflow in a knowledge graph-specific language. The structured file is deployed to a knowledge graph execution engine.