Abstract: Inference results of a machine learning model and associated inputs are collected. An inference request is received. A determination is made whether a request input of the inference request matches at least one collected input of a set of collected inputs. In response to determining that the request input matches at least one collected input in the set of collected inputs, an inference result is determined using one or more collected inference results associated with said one or more matching inputs in the set of collected inputs.

Abstract: A method, a computer program product, and a system for scheduling a first query execution plan for executing a first query for accessing first data sets of data of a relational database system (RDBS) and a second query execution plan for executing a second query for accessing second data sets of the data. The data is divided into data blocks of data sets of the data, wherein metadata of the RDBS comprises respective information about at least one property of the data sets of a respective data block of the data blocks. The scheduling may be performed on the basis of an examination if there is a common partition between a first partition of data blocks which may fulfill a first condition according to the first query and a second partition of data blocks which may fulfill a second condition according to the second query.

Abstract: Methods and systems are provided for tuning memory allocated among a plurality of applications in a data processing system. In one implementation, the method includes generating memory benefit data for the plurality of applications, comparing the generated memory benefit data associated with each of the plurality of applications, and dynamically reallocating memory from one or more of the plurality of applications to one or more other of the plurality of applications based on the comparison. A method and system is also provided for tuning memory allocated among a plurality of individual memory consumers for a given application.

Abstract: A method and system for improving memory access patterns of software systems on NUMA systems discovers NUMA system resources where the NUMA system resources comprises a plurality of NUMA nodes; determines a plurality of database threads, processes, and objects for a database configuration; and generates a policy which assigns the plurality of database threads, processes, and objects to the plurality of NUMA nodes, wherein the generating of the policy is performed prior to initialization of the plurality of database threads, processes, and objects. The assignment of the database threads, processes, or objects to NUMA nodes is such that the amount of remote memory accesses is reduced. When the database thread, process, or object initializes, the database server queries the policy for its assigned NUMA node(s). The database thread, process, or object is then bound to the assigned NUMA node(s).