Abstract: Data from data sources may be processed at an edge device. The edge device may generate a local processing result, filter the data, and/or prioritize the data. Accordingly, data is transmitted from the edge device to the data platform, where it may be processed further. For example, a local processing result may be processed at the data platform, such that processing is performed without all of the data source data. In examples, at least a part of such data may remain at an edge device. The edge device may maintain a manifest of data stored by the edge device. The data platform may generate an aggregated manifest using manifests from associated edge devices, such that it may be determined where data is stored. As a result, the data platform may redirect requests to an associated edge device when it is determined that requested data is remote from the data platform.

Abstract: Data from data sources may be processed at an edge device. The edge device may generate a local processing result, filter the data, and/or prioritize the data. Accordingly, data is transmitted from the edge device to the data platform, where it may be processed further. For example, a local processing result may be processed at the data platform, such that processing is performed without all of the data source data. In examples, at least a part of such data may remain at an edge device. The edge device may maintain a manifest of data stored by the edge device. The data platform may generate an aggregated manifest using manifests from associated edge devices, such that it may be determined where data is stored. As a result, the data platform may redirect requests to an associated edge device when it is determined that requested data is remote from the data platform.

Abstract: Methods, storage media, and systems for translating a software expression from a user application programming interface (API) call to an API call of a software development kit (SDK) are disclosed. Some examples may include: receiving a tagged expression indicating that a translation of the software expression from a user API call to an API call of an SDK is to be performed, the SDK being associated with a cloud-native high-performance computing environment, processing an abstract syntax tree associated with the software expression, the processing including replacing symbols in the abstract syntax tree with respective variables, replacing a return statement in the abstract syntax tree with a serialization instruction to write a result to local storage, and serializing the processed abstract syntax tree and providing the serialized abstract syntax tree and one or more resource files to the cloud-native high-performance computing environment for execution.

Abstract: Methods, storage media, and systems for translating a software expression from a user application programming interface (API) call to an API call of a software development kit (SDK) are disclosed. Some examples may include: receiving a tagged expression indicating that a translation of the software expression from a user API call to an API call of an SDK is to be performed, the SDK being associated with a cloud-native high-performance computing environment, processing an abstract syntax tree associated with the software expression, the processing including replacing symbols in the abstract syntax tree with respective variables, replacing a return statement in the abstract syntax tree with a serialization instruction to write a result to local storage, and serializing the processed abstract syntax tree and providing the serialized abstract syntax tree and one or more resource files to the cloud-native high-performance computing environment for execution.

Abstract: In a numerical simulation, input data expressed in at least a first domain is received. The input data is transformed to generate frequency modes of the input data in frequency domain. The transformed data is down-sampled to retain a subset of the frequency modes in the frequency domain. The down-sampled data is successively processed with one or more stages of a neural network to generate a down-sampled output in the frequency domain. The processing includes applying, in each stage of the one or more stages, a non-linear transformation to the subset of the frequency modes. The down-sampled output is then up-sampled to generate an up-sampled output corresponding to the frequency modes in the frequency domain, and the up-sampled output is transformed from the frequency domain to the at least the first domain to generate a result of the numerical simulation.

Abstract: In a numerical simulation, input data expressed in at least a first domain is received. The input data is decomposed into at least i) low-pass filtered data that captures a low-pass filtered version of the input data in the at least the first domain and ii) high-pass filtered data that captures a high-pass filtered version of the input data in the at least the first domain. The low-pass filtered data is transformed to frequency domain, and weights are applied to the low-pass filtered data in the frequency domain to generate weighted low-pass filtered data in the frequency domain. The weighted low-pass filtered data is transformed from the frequency domain to the at least the first domain, and output data for the numerical simulation is composed based on at least the weighted low-pass filtered data in the at least the first domain.

Abstract: Data from data sources may be processed at an edge device. The edge device may generate a local processing result, filter the data, and/or prioritize the data. Accordingly, data is transmitted from the edge device to the data platform, where it may be processed further. For example, a local processing result may be processed at the data platform, such that processing is performed without all of the data source data. In examples, at least a part of such data may remain at an edge device. The edge device may maintain a manifest of data stored by the edge device. The data platform may generate an aggregated manifest using manifests from associated edge devices, such that it may be determined where data is stored. As a result, the data platform may redirect requests to an associated edge device when it is determined that requested data is remote from the data platform.

Abstract: Methods, storage media, and systems for translating a software expression from a user application programming interface (API) call to an API call of a software development kit (SDK) are disclosed. Some examples may include: receiving a tagged expression indicating that a translation of the software expression from a user API call to an API call of an SDK is to be performed, the SDK being associated with a cloud-native high-performance computing environment, processing an abstract syntax tree associated with the software expression, the processing including replacing symbols in the abstract syntax tree with respective variables, replacing a return statement in the abstract syntax tree with a serialization instruction to write a result to local storage, and serializing the processed abstract syntax tree and providing the serialized abstract syntax tree and one or more resource files to the cloud-native high-performance computing environment for execution.