ACAT 2017 Seattle

The next ACAT1 “AI Reloaded” with a strong emphasis in Artificial Intelligence in Physics Research will be held in Seattle August 21-25 2017 (see here for more, ACAT Poster).   Join us…

Scientific Programme

1) Computing Technology for Physics Research

  • This track includes topics that impact how we do physics analysis and research that are related to the enabling technology. Here is a fairly detailed list of possibilities (which isn’t, of course, complete!).

    • Languages, Software quality, IDE and User Interfaces
      • Languages (new C++ standard, Java, …), language interoperability, code portability
      • Software quality assurance; code reflection; documentation, performance and debugging tools
      • Computer system Benchmarking, beyond Linpack
      • IDE and frameworks
      • User Interfaces, Common Libraries.
    • Distributed and Parallel Computing
      • Multilevel parallelism
      • Distributed computing
      • GRID and Cloud computing
    • Architectures
      • New architectures
      • Massive Multicore
      • High Performance Computing
      • Accelerator-based computing (GPGPU’s, FPGA’s)
      • High and low precision floating-point (quad/octuple precision and short float for CUDA)
    • Virtualization
      • Containerization (shifter, remote scripting)
      • Hardware abstraction
      • Clouds
    • Networking
      • New TCP control and routing mechanism
      • Alternative to ethernet
    • Online computing
      • Advanced Monitoring, Diagnostics and Control
      • Scalable distributed data collectors
      • High Level Triggering (HLT)
      • Stream event processing & High Throughput Computing (HTC)

        2) Data Analysis – Algorithms and Tools

        There are as many different algorithms and methods as their are physicists. Obviously, we can’t list them all here, but here are some broad outlines of techniques that fit into this category. Of course, new and novel categories are part of what this conference is looking for.

        • Machine Learning
          • Neural Networks and Other Pattern Recognition Techniques
          • Evolutionary and Genetic Algorithms
          • Package Benchmarking
          • Automation of Science: Data to formula
        • Advanced Data Analysis Environments
          • Statistical Methods, Multivariate analysis
          • Data mining
        • Simulation, Reconstruction and Visualization Techniques
          • New algorithms for finding tracks, or other objects.
          • Detector and Accelerator Simulations, MC and fast MC
            Reconstruction Algorithms
          • Visualization Techniques; event displays
        • Advanced Computing
          • Quantum Computing
          • Bio Computing: life process simulation, brain simulation, quantum biology

            3) Computations in Theoretical Physics: Techniques and Methods

            This track focuses on computing techniques and algorithms used in the theoretical side of physics research.

            • Automatic Systems
              • Automatic Computation Systems: from Amplitudes to Event Generators
              • Multi-dimensional Integration: Methods and Tools
              • Intensive High Precision Numerical Computations: Algorithms and Systems
            • Higher orders
              • Matching NLO and NNLO calculations to event generators
              • Multi-loop Calculations and Higher Order Corrections
            • Computer Algebra Techniques and Applications
            • Computational physics, Theoretical and simulation aspects
              • Lattice QCD,
              • Cosmology, Universe Large Scale Structure, Gravitational waves
              • Nuclear physics N-body computation,
              • Plasma physics,
              • Earth Physics, climate, earthquakes
  1. Advanced Computing and Analysis Technology in Physics Research

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