Since 1985, the CHEP Conference series has covered all aspects of computational challenges in High Energy and Nuclear Physics. With evolving needs, trends, requirements and products, CHEP is the main event at which new computing technology including new software, new hardware architectures and algorithmic strategies are presented and discussed. Proceedings from the conference series have long played a significant role in informing the community about new trends and directions in computing for HEP.

In recent and coming years, HEP will be more than ever a Big Data Science, and as such, following the trend in industry, machine learning and intelligence are increasingly being used. Contributions from CHEP are therefore welcome in our journal section and with this Frontiers Research Topic, we wish to promote some major contributions to extended papers, as was done in previous CHEP editions. In order to provide an overview of major trends in the field, we invite submissions on topics thereafter, along the tracks of the scientific program of the conference, but not limited to:

• Data processing. HEP is notoriously a big data science, and requires state-of-the-art systems for real-time data processing as well as efficient simulation and reprocessing algorithms.
• Cloud computing. Due to globalization of funding and the high needs for computing, computing in HEP is largely distributed over world wide computing grids, growingly including exascale facilities, with heterogeneous hardware. The virtualization of a computing center demands for a state-of-the-art data management system.
• Data analysis methods. In order to produce and analyze the large amount of HEP data and simulation, the community never stopped developing algorithms and software, with an upticking trend of including artificial intelligence and quantum algorithms.
• Computing hardware. After decades of CPU dominance, more efficient computing substrate is required, leading to accelerating usage in HEP of exascale facilities, heterogeneous platforms of various accelerators, including quantum computers in foremost R&D.
• Maintainability. Software maintenance and sustainability is a crucial element of deploying new algorithms and technologies. Adequate education and outreach programs need to be in place with the HEP community to attract and retain skilled driving forces.

We solicit submissions of manuscripts, including results from original research introduced in the conference proceedings.

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Frontiers in Big Data

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