International Business Machines Corporation

Sap Se

Peng Xue

Lei Tian

Yi Shao

Jing James Xu

Peng Hui Jiang

Wei Wu

Di Ling Chen

Oliver Patrick Schmidt

Jian-ping Hui

Andreas Ludwig Erz

Steffen Lammel

Various embodiments for a thread management system are described herein. An embodiment operates by determining that one or more scheduler threads of a server are allocated from a shared memory. A request to spawn a native thread at the server is received. The request is intercepted and an override for the request in which the resources for spawning the native thread are requested from the shared memory is executed. An allocation of resources for spawning and executing the native thread is received from the shared memory. An error on the server is detected. The shared memory is dumped into a dump file responsive to determining the error. The dump file includes an indication of what threads were allocated from the shared memory. The one or more scheduler threads and the native thread are restarted after the dumping.

Thread management system

Methods, systems, and computer-readable storage media for requesting, from a domain name system (DNS) server within an enterprise network, an IP address for a DNS name associated with a computing device, receiving the IP address, storing the IP address in a speculative DNS cache, the speculative DNS cache being operable to store IP addresses for a set of DNS names including the DNS name, providing, by the speculative DNS cache, a refresh period for the IP address, and determining that the refresh period of the IP address has tolled, and in response, refreshing the IP address in the speculative DNS cache.

Speculative domain name system cache

Methods, computer program products, and systems are presented. The methods include, for instance: obtaining a request for a predicted ensemble score in real-time. A subset of base model instances is formed by use of a preconfigured priority policy. A fitness score of the formed subset, quantifying the accuracy of the subset, is calculated as a sum of weights respective to the base model instances in the subset. A number of base models represented in the subset is less than or equal to a number of all based models.

Real time ensemble scoring optimization

An approach to optimizing predictive model analysis, comprising creating one or more model templates, decomposing a predictive model, wherein model information is extracted from the predictive model, storing the model information in the one or more model templates, creating a plurality of sub-models, associated with the predictive model, using the stored model information, sending the plurality of sub-models to a scoring engine, receiving results based on the plurality of sub-models from the scoring engine and generating predictions based on combining the results received from the scoring engine. The generated predictions can be sent to one or more analytic applications for further processing.

Predictive analysis with large predictive models

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Xi'an, China

Peng Xue