International Business Machines Corporation

Semiconductor Manufacturing International (shanghai) Corporation

Semiconductor Manufacturing International (beijing) Corporation

Hui Qing Shi

Yi Bin Wang

Wei Wang

Qing Feng Zhang

Yuan Yuan

Ya Pei Zhou

Xue Feng Gao

Michael H Dawson

Graham Alan Chapman

Oluwatobi Ajila

San Hong Li

Zhi Feng Zhao

Shuhui Chen

Yu Fen Yuan

Chao Yu

James C Thorburn

Shi Xin Ruan

Hongjun Yu

Pan Ding

A method for event identification including receiving event information pertaining to events occurring with respect to a computing environment, each event having a measurement metric; evaluating by a probability function the measurement metric for each event to determine when the measurement metric is above a predetermined probability threshold or below a probability threshold wherein above a probability threshold or below a probability threshold is classified as alarm data; processing the alarm data through a decision tree to determine based on historical data when the alarm data is significant or when the alarm data is not significant and to reduce the number of alarm data to a predetermined number of significant alarm data; and displaying the predetermined number of significant alarm data to a user.

Event identification through machine learning

Analyzing software change impact is provided. Feedback is received regarding a predicted impact of a software change to a set of components of a service. It is determined whether the predicted impact of the software change is correct based on the feedback. In response to determining that the predicted impact of the software change is correct based on the feedback, the software change is applied to the set of components of the service increasing performance of the service and a server computer hosting the service.

Analyzing software change impact based on machine learning

Intelligent information adapter generation for service management. Managing selection of adapters from and adapter pool to use for collecting the service management information includes, based on adding a data source, selecting an adapter to use for collecting service management information from the added data source, the selecting including automatically creating and selecting a new adapter, the new adapter being created based on access information to access the added data source, a resource type of the portion of service management information collected from the added data source, and a desired performance indicator that the new adapter is to parse out from the portion of service management information that the new adapter collects.

Intelligent information adapter generation for service management

Cognitively detecting cloud services and their associated status of a Virtual Machine and/or Container in a cloud platform to predict availability of cloud services preferably including the status of the services, a service object health map, and a service health status. The outputs are preferably sent to a user for feedback, which is sent back to the cognitive service.

Cognitive method for detecting service availability in a cloud environment

An approach is provided for orchestrating computing resources between different computing environments. Data from first and second computing environments is monitored. The data specifies utilization of infrastructure, middleware, software testing tools, integrated development environments (IDEs), relationships among nodes, utilization of the nodes, and user behavior in the first and second computing environments. Based on the utilization of the infrastructure, middleware, tools, IDEs, node relationships and utilization, and user behavior, a pattern decision tree is updated, and unbalanced workloads are identified. Based on a comparison of the unbalanced workloads to patterns in the updated pattern decision tree, an orchestration topology is generated that specifies a new placement of the computing resources in the first and second computing environments. Based on the orchestration topology, computing resource(s) are automatically deployed in the first computing environment and other computing resource(s) are automatically deployed in the second computing environment.

Orchestrating computing resources between different computing environments

A microphone and its manufacturing method, relating to semiconductor techniques. The microphone comprises a capacitor comprising of a back plate and a vibration film plate, with the vibration film plate comprising a plurality of holes. The holes in the vibration film plate provide a ventilation route for pressured air in the microphone, and thus reduce the pressure on the vibration film plate which otherwise is susceptible to damaged under high air pressure. This inventive concept improves a microphone's acoustic tolerance.

Microphone and manufacture thereof

A microphone includes a substrate, an opening in the substrate, and a support structure in the opening. The support structure includes a first bracket formed in a closed-loop pattern and a second bracket connecting the first bracket to a periphery of the opening. The support structure in the opening increases the mechanical reliability of the microphone.

MEMS microphone and method for manufacturing the same

An apparatus for optimizing network traffic which includes a host computer having virtual machines (VMs); a monitoring module to collect network traffic data from the VMs; an analysis engine to receive the network traffic data from the monitoring module and to calculate metric values pertaining to the network traffic data; a pattern module to store network traffic patterns having metric values and to provide the network traffic patterns to the analysis engine, the analysis engine compares the calculated metric values to the network traffic pattern metric values and provides an output of a result of the compare of the calculated metric values to the network pattern metric values; and responsive to receipt of the output from the analysis engine, an optimization module processes the output and provides an optimization action to the VMs to improve the flow of the network traffic between the VMs.

Automatically optimizing network traffic

An approach is provided for orchestrating computing resources between different computing environments. Data from first and second computing environments is monitored. The data specifies utilization of infrastructure, middleware, software testing tools, integrated development environments (IDEs), relationships among nodes, utilization of the nodes, and user behavior in the first and second computing environments. Based on the utilization of the infrastructure, middleware, tools, IDEs, node relationships and utilization, and user behavior, a pattern decision tree is updated. Based on the updated pattern decision tree and a user request that specifies requirements of the computing resources, an orchestration topology is generated that specifies a placement of the computing resources in the first and second computing environments. Based on the orchestration topology, computing resource(s) are automatically deployed in the first computing environment and other computing resource(s) are automatically deployed in the second computing environment.

In an approach for removing tenant initialization check per tenant for compiled code, a processor receives a request to create a tenant. A processor creates the tenant. A processor marks a current thread of the tenant as not eligible to run just-in-time (JIT) code, wherein the marking indicates that when a method is invoked, a non-JIT version of the method is executed. A processor executes initialization of a first class from an optimization list, wherein the optimization list is a configurable list of classes to be initialized prior to running JIT code. A processor determines that class initialization has been executed for all classes on the optimization list. A processor adjusts the marking to indicate that the current thread is eligible to run JIT code and that the tenant may run JIT code that assumes, without checking, that classes on the optimization list are initialized.

Growing community of inventors

Beijing, China

Hui Qing Shi