Patent classifications
G06F16/903
Device profiling in GPU accelerators by using host-device coordination
System and method of compiling a program having a mixture of host code and device code to enable Profile Guided Optimization (PGO) for device code execution. An exemplary integrated compiler can compile source code programmed to be executed by a host processor (e.g., CPU) and a co-processor (e.g., a GPU) concurrently. The compilation can generate an instrumented executable code which includes: profile instrumentation counters for the device functions; and instructions for the host processor to allocate and initialize device memory for the counters and to retrieve collected profile information from the device memory to generate instrumentation output. The output is fed back to the compiler for compiling the source code a second time to generate optimized executable code for the device functions defined in the source code.
Automated honeypot creation within a network
Systems and methods for managing Application Programming Interfaces (APIs) are disclosed. Systems may involve automatically generating a honeypot. For example, the system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving, from a client device, a call to an API node and classifying the call as unauthorized. The operation may include sending the call to a node-imitating model associated with the API node and receiving, from the node-imitating model, synthetic node output data. The operations may include sending a notification based on the synthetic node output data to the client device.
Regular expression generation using span highlighting alignment
Techniques for generated regular expressions are disclosed. In some embodiments, a regular expression generator may receive input data comprising one or more character sequences. The regular expression generator may convert character sequences into a sets of regular expression codes and/or span data structures. The regular expression generator may identify a longest common subsequence shared by the sets of regular expression codes and/or spans, and may generate a regular expression based upon the longest common subsequence. Alignment of span data structures may be performed when generating the regular expression.
MACHINE LEARNING METHOD AND NAMED ENTITY RECOGNITION APPARATUS
A computer divides a character string included in text data into a plurality of tokens. The computer searches, by performing matching processing between a token string indicating a specific number of consecutive tokens among the plurality of tokens and dictionary information including a plurality of named entities, the plurality of named entities for a similar named entity whose similarity to the token string is equal to or more than a threshold. The computer converts matching information indicating a result of the matching processing between the token string and the similar named entity into first vector data. The computer generates input data by using a plurality of pieces of vector data converted from the plurality of tokens and the first vector data. The computer generates a named entity recognition model that detects a named entity by performing machine learning using the input data.
MACHINE LEARNING METHOD AND NAMED ENTITY RECOGNITION APPARATUS
A computer divides a character string included in text data into a plurality of tokens. The computer searches, by performing matching processing between a token string indicating a specific number of consecutive tokens among the plurality of tokens and dictionary information including a plurality of named entities, the plurality of named entities for a similar named entity whose similarity to the token string is equal to or more than a threshold. The computer converts matching information indicating a result of the matching processing between the token string and the similar named entity into first vector data. The computer generates input data by using a plurality of pieces of vector data converted from the plurality of tokens and the first vector data. The computer generates a named entity recognition model that detects a named entity by performing machine learning using the input data.
AUTOMATED INTEROPERATIONAL TRACKING IN COMPUTING SYSTEMS
Techniques of automated interoperation tracking in computing systems are disclosed herein. One example technique includes tokenizing a first event log from a first software component and a second event log from the second software component by calculating frequencies of appearance corresponding to strings in the first and second event logs and selecting, as tokens, a first subset of the strings in the first event log and a second subset of the strings in the second event log individually having calculated frequencies of appearance above a preset frequency threshold. The example technique can also include generating an overall event log for a task executed by both the first and second software components by matching one of the strings in the first subset to another of the strings in the second subset.
ONLINE OPTIMAL CONTROL UNDER CONSTRAINTS
Embodiments of the present invention provide computer-implemented methods, computer program products and computer systems. Embodiments of the present invention can identify a plurality of constraints on states of data and actions of data associated with a data model. Embodiments of the present invention can then identify constraints on safety policy parameters associated with a computing device. Embodiments of the present invention can then convert the identified constraints into a uniform domain syntax that considers coupled and decoupled constraints and introduce buffer data within the converted constraints, wherein the buffer data filters outlier constraints within the plurality of constraints. Embodiments of the present invention can then dynamically generate optimal safety policies associated with the computing device based on the remaining constraints.
ONLINE OPTIMAL CONTROL UNDER CONSTRAINTS
Embodiments of the present invention provide computer-implemented methods, computer program products and computer systems. Embodiments of the present invention can identify a plurality of constraints on states of data and actions of data associated with a data model. Embodiments of the present invention can then identify constraints on safety policy parameters associated with a computing device. Embodiments of the present invention can then convert the identified constraints into a uniform domain syntax that considers coupled and decoupled constraints and introduce buffer data within the converted constraints, wherein the buffer data filters outlier constraints within the plurality of constraints. Embodiments of the present invention can then dynamically generate optimal safety policies associated with the computing device based on the remaining constraints.
Tenant-isolated custom annotations for search within a public corpus
Annotations are customized for a tenant-specific search within a public corpus. In a non-limiting embodiment of the invention, a cartridge file is received by a semantic search application. The cartridge file includes a new attribute definition that is not available in an index of the semantic search application. The new attribute definition is incorporated within the index based on an approximation of one or more existing attributes in the index. One or more documents are retrieved from the public corpus based on a concept search using the incorporated new attribute definition and the one or more documents are annotated based on the incorporated new attribute definition. The annotated one or more documents are stored in a tenant-specific dataset separate from the public corpus.
Secure analytics using homomorphic and injective format-preserving encryption
Secure analytics using homomorphic and injective format-preserving encryption are disclosed herein. An example method includes encoding an analytic parameter set using a homomorphic encryption scheme as a set of homomorphic analytic vectors; transmitting the set of homomorphic analytic vectors to a server system; and receiving a homomorphic encrypted result from the server system, the server system having utilized the homomorphic encryption scheme and a first injective, format-preserving encryption scheme to evaluate the set of homomorphic analytic vectors over a datasource.