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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Article
LBL Publications (2005)
The very largest parallel particle simulations, for problems involving six dimensional phase space, generate vast quantities of data. It is desirable to store such enormous datasets efficiently and also to share data effortlessly between data analysis tools such as PartView~\cite FPAT082 and extensions to AVS/Express among other groups who are working on particle-based accelerator simulations. We define a very simple file schema built on top of HDF5~\cite hdf5hp (Hierarchical Data Format version 5) as well as an API that simplifies the reading/writing of the data to the HDF5 file format. HDF5 offers a self-describing machine-independent binary file format that supports scalable parallel I/O performance for MPI codes on computer systems ranging from laptops to supercomputers. The sample H5PartAPI is available for C, C++, and Fortran codes. The common file format will enable groups that using completely different simulation implementations to transparently share datasets and custom data analysis tools like Part View. We will show examples and benchmark data for various platforms.
    Cover page: H5Part: A Portable High Performance Parallel Data Interface for Particle Simulations
    • Article
    Lawrence Berkeley National Laboratory (2008)

    Significant problems facing all experimental and computationalsciences arise from growing data size and complexity. Common to allthese problems is the need to perform efficient data I/O on diversecomputer architectures. In our scientific application, the largestparallel particle simulations generate vast quantities ofsix-dimensional data. Such a simulation run produces data for anaggregate data size up to several TB per run. Motived by the need toaddress data I/O and access challenges, we have implemented H5Part, anopen source data I/O API that simplifies the use of the Hierarchical DataFormat v5 library (HDF5). HDF5 is an industry standard for highperformance, cross-platform data storage and retrieval that runs onall contemporary architectures from large parallel supercomputers tolaptops. H5Part, which is oriented to the needs of the particlephysics and cosmology communities, provides support for parallelstorage and retrieval of particles, structured and in the future unstructuredmeshes. In this paper, we describe recent work focusing on I/O supportfor particles and structured meshes and provide data showing performance on modernsupercomputer architectures like the IBM POWER 5.

      Cover page: Progress on H5Part: A Portable High Performance Parallel Data Interface for Electromagnetics Simulations
      • Article
      LBL Publications (2003)
        Cover page: The CMEE library for numerical modeling of electron effects
        • Article
        LBL Publications (2022)
        The computational cost for high energy physics detector simulation in future experimental facilities is going to exceed the current available resources. To overcome this challenge, new ideas on surrogate models using machine learning methods are being explored to replace computationally expensive components. Additionally, differentiable programming has been proposed as a complementary approach, providing controllable and scalable simulation routines. In this document, new and ongoing efforts for surrogate models and differential programming applied to detector simulation are discussed in the context of the 2021 Particle Physics Community Planning Exercise (`Snowmass').
          Cover page: New directions for surrogate models and differentiable programming for High Energy Physics detector simulation
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