INAF.Libraries.Net.Data.Helpers TECHNICAL REPORT

This solution provides a set of reusable .NET libraries for scientific and numeric data processing, with a focus on multidimensional data structures, matrix-oriented transformations, and parallel execution helpers. The codebase is organized into small libraries with separated responsibilities:- `INAF.Libraries.Net.Data`: domain types and low-level data access for matrices, qubes, headers, and typed result containers.- `INAF.Libraries.Net.Data.Helpers`: higher-level helper APIs for building arrays and matrices, and for converting `Qube` data into analysis-ready `Matrix` instances.- `INAF.Libraries.Net.Parallelization`: reusable parallel iteration and processor allocation helpers used by the other libraries.The solution is suitable as a foundation for data-analysis pipelines that need to read structured scientific datasets, transform them into matrix form, and execute CPU-bound operations efficiently

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-24
DOI
https://doi.org/10.5281/zenodo.19204096
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

INAF.Libraries.Net.Data.Helpers TECHNICAL REPORT

Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
article

INAF.Libraries.Net.Data.Helpers TECHNICAL REPORT

article en

Abstract

This solution provides a set of reusable .NET libraries for scientific and numeric data processing, with a focus on multidimensional data structures, matrix-oriented transformations, and parallel execution helpers. The codebase is organized into small libraries with separated responsibilities:- `INAF.Libraries.Net.Data`: domain types and low-level data access for matrices, qubes, headers, and typed result containers.- `INAF.Libraries.Net.Data.Helpers`: higher-level helper APIs for building arrays and matrices, and for converting `Qube` data into analysis-ready `Matrix` instances.- `INAF.Libraries.Net.Parallelization`: reusable parallel iteration and processor allocation helpers used by the other libraries.The solution is suitable as a foundation for data-analysis pipelines that need to read structured scientific datasets, transform them into matrix form, and execute CPU-bound operations efficiently

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Parallel Computing and Optimization Techniques
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INAF.Libraries.Net.Data.Helpers TECHNICAL REPORT · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS