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AICS Cafe

AICS Cafe is a place where the researchers in AICS can frankly discuss about their researches beyond their own disciplinary wall in order to collaborate with each other. We plan to have it twice a month regularly. We welcome all people including the promotion office and administration division of K computer in AICS.

  • Purpose : In order to promote the research collaboration beyond each of existing research disciplines, this seminar provides the discussion field for exchanging information, understanding neighboring researchers, and collaboration between each other.
  • Place: Workshop room (6th floor) at AICS
  • Lang : presentation in Japanese or English, the slide in English
  • Etc.: Please give your presentations clearly to researchers in other fields. Please do not hesitate to ask a question to the speakers.

The 110th AICS Cafe
Date and Time: Wed. Apr. 5, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: How to raise our own worth: A theory from Adlerian psychology
Speaker: Sachiyo Ikeda (Research support devision, Helth center)

Presentation Language: Japanese
Presentation Material: Japanese

    Abstract:
I have low self-esteem. Actually the results of tests for measuring self-esteem show that my self-esteem is low level. In such circumstances, I have been interested in raising my self-esteem. On one occasion, I met with an Adlerian psychological literature named “The Courage of Being Disliked”, and I found three important keywords many times: proprioception, contributions of others and trusting of others, in it. Adler said that the contribution of others is an essential part in raising one’s worth. What is the “contribution of others”? I would like to introduce the Adlerian psychology and discuss the issue with computational scientists.

The 109th AICS Cafe
Date and Time: Wed. Mar. 22, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Fixed-mesh method for solid/structure simulation: past, present and future
Speaker: Koji Nishiguchi (Complex Phenomena Unified Simulation Research Team)

Presentation Language: English
Presentation Material: English

    Abstract: Detail

For the last several decades, Lagrangian finite element methods, which use deformed-mesh, have been the de facto standard for solid/structure simulations. This method can track the surface of solid with high accuracy and compute constitutive relation of solid with ease, since a geometric domain of the solid is spatially discretized using unstructured mesh which conforms to the deforming solid.
On the other hand, an Eulerian finite element method for solid/structure mechanics was proposed in the early 1990s. This method uses spatially fixed mesh and thus allows solid material to flow through the mesh. In this context, compared to Lagrangian finite element methods (Deformed-mesh methods), Eulerian finite element methods (Fixed-mesh methods) are attractive for computing large deformation problems, computing fracture problems, and generating computational mesh easily.
Utilizing the above advantages, Eulerian finite element methods have been applied for bullet impact analysis, solid-fluid interaction analysis, soft adhesive analysis, and soft resin analysis. However, the computational challenges have been their expensive computational cost, the diffusion of the solution due to the advection, and the modeling of contact interfaces. In my presentation, I will explain the past, present and future studies of fixed-mesh methods for solid/structure mechanics.

The 108th AICS Cafe
Date and Time: Wed. Mar. 15, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Parallel Image Compositing on Massively Parallel Rendering Environments
Speaker: Jorji Nonaka (Advanced Visualization Research Team)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

Sort-last visualization approach has become the defacto standard for massively parallel rendering environments. In this approach, the entire set of the images generated by the rendering nodes needs to be combined into a single final image, and for this purpose, parallel image compositing algorithms which try to minimize the idle time of the nodes have been widely used. As the number of nodes increases, the parallel rendering processes can have their workload reduced. However, for the parallel image compositing process, the workload increases proportionally with the increase in the number of rendering nodes, which is similar to the weak scaling case. In this talk, I will present the parallel image compositing library, named 234Compositor, primarily developed for the HIVE visualization application which works on the K computer massively parallel environment.

The 107th AICS Cafe
Date and Time: Wed. Feb. 15, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: How accurate are the weather forecast simulations? Let’s check it!
Speaker: Taeka Awazu (Data Assimilation Research Team)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

How should the rain forecast simulations be evaluated when we compare the simulations with the observation data? Is it possible to evaluate the simulations comprehensively by the shape and location of rainfall areas? The commonly used verification methods for the rain forecast have difficulties to evaluate the shape and location error of the rainfall areas. If the forecast has location errors even though the shape of rainfall areas is predicted perfectly, these methods evaluate the forecast lower. This evaluation does not match with our intuition.
Therefore, we propose a new verification method for the rain forecast using the shape and location of the rainfall areas. In this method, to mimic the human recognition, the close rainfall areas are combined, and the features of shape and location of the rainfall areas in the combined areas are computed. The proposed method can evaluate the shape and location error that cannot be evaluated by the frequently used methods. Additionally, by using the visualization with colors, this method can verify the rain forecast intuitively.

The 106th AICS Cafe
Date and Time: Wed. Feb. 8, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Fast Evaluation of Two-Electron Integrals using Pseudospectral Methods
Speaker: Keisuke Sawada (Computational Molecular Science Research Tea)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

A fast estimation of two-electron repulsive integrals (ERIs) is an important and imperative subject in any ab-initio quantum chemical calculations. Since the computational cost of the ERIs formally increases as N4, where N is the number of basis functions, we often suffer from much time-consuming estimations in large molecular systems.
In order to address the tough problem, several methodologies have been developed to date. Among them, the pseudospectral (PS) method is a strong candidate for a quick and efficient evaluation of the ERIs. In the PS method, one analytical integral is replaced by a numerical summation consisting of discrete grid points and the computational cost is reduced from O(N4) to O(MN2), where M is the number of grid points.
In this study, we implement the PS method into our NTChem program and investigate the performances of this method using the MPI/OpenMP hybrid parallelized code. In large molecular system which includes more than 8,000 basis sets, we find that the PS method shows a good scaling with respect to used CPU cores and becomes much faster than the analytic integral methods.

The 105th AICS Cafe
Date and Time: Wed. Feb. 1, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Exploring data assimilation for plants
Speaker: Hazuki Arakida (Data Assimilation Research Team)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

Vegetation models simulate functions of plants such as carbon and water exchanges between the atmosphere and land surface, and play an essential role in climate simulations. However, the vegetation models have large uncertainties. For example, it is very difficult to simulate accurately the dates when the leaves grow and fall. Data assimilation combines the simulation with actual observations, and can reduce those uncertainties.
We developed a data assimilation system with a vegetation model known as the SEIB-DGVM (Spatially Explicit Individual Base Dynamic Global Vegetation Model). As the first step, an experiment was performed at a single location in Eastern Siberia by assimilating satellite-observed leaf area data. The results showed that the growth and decay of the leaves, carbon cycles and the parameters of the tree and grass were successfully estimated. As the second step, the experiment was expanded to multiple locations in Eastern Siberia. The results were promising.

The 104th AICS Cafe
Date and Time: Wed. Jan. 18, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Integrated meshing-and-analysis approach for fast-and-robust unstructured finite-element earthquake simulations
Speaker: Kohei Fujita (Computational Disaster Mitigation and Reduction Research Unit)

Presentation Language: English
Presentation Material: English

    Abstract: Detail

Unstructured finite-element methods are widely used in earthquake simulations for accurate modeling of complex three-dimensional geometry and nonlinear material properties. However, its applicability to large-scale problems is often limited by the difficulty of generating high quality mesh and large analysis cost. To overcome these difficulties, we have been developing robust mesh generators and fast analysis methods in an integrated approach. In this talk, I will show Tera Degrees-of-Freedom scale unstructured finite-element earthquake simulations enabled by using the developed method on the full K computer.

The 103rd AICS Cafe
Date and Time: Wed. Jan. 11, 2017, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Turbulence in Atmospheric Simulations
Speaker: Seiya Nishizawa (Computational Climate Science Research Team)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

There exist various spatiotemporal scale phenomena in the atmospheric variability, and they interact with each other. Atmospheric turbulence is small scale variability, and plays an important role in the larger scale phenomena. Because of its small scale, it has been difficult to represent the turbulence directly in atmospheric simulations, so far. The effects of turbulence on large scale phenomena have been taken into account through parameterizations based on empirical rules in simulations. As the development of computers, it has become possible to represent the turbulence in the simulations. I will introduce the importance of the turbulence in the atmospheric variability, and our study on representation of the turbulence in the simulations.

The 102nd AICS Cafe
Date and Time: Wed. Nov. 16, 2016, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Assembling a library of 2D projection images from 3D biological shapes to resolve XFEL data
Speaker: Sandhya Tiwari (Computational Structural Biology Research Unit)

Presentation Language: English
Presentation Material: English

    Abstract: Detail

X-ray free electron laser (XFEL) scattering experiments has been described as the future of structural biology. The technique has several advantages, including its ability to probe a single particle sample without the need for crystallisation, and to produce diffraction data before the sample is destroyed by radiation. However, resolving structures from XFEL diffraction patterns can be challenging due to the phase problem. Considering the novelty of the technique, there is also limited data available to provide initial models that fit new diffraction patterns. Therefore, we consider a strategy to provide efficient interpretation of XFEL data by searching them against a database of hypothetical biological shapes to obtain an initial structural model. To build a database of biological shapes, we assemble various three-dimensional (3D) structures in existing structure databanks, such as the Electron Microscopy Data Bank (EMDB). We can then reduce the assembled dataset to a minimal yet distinct set of hypothetical biological shapes. In the first part of this assembly, we present the analysis of single particle cryo-electron microscopy (cryo-EM) structures. Here, we analyse the variation in the shapes that exists within the 3D cryo-EM maps, and within their simulated two-dimensional (2D) projection images. This analysis provides us with the extent to which 2D images of two distinct 3D shapes can be similar, giving us an idea of the expected degeneracy when we compare experimental data to a hypothetical biological shape. In general, we expect that with a sufficient number of 3D shapes will allow us to provide candidate models for new XFEL data effectively.

The 101st AICS Cafe
Date and Time: Wed. Nov. 9, 2016, 15:30-16:30
Place: Workshop room (6th floor) at AICS

Title: Large ensemble data assimilation with atmospheric models
Speaker: Keiichi Kondo (Data Assimilation Research Team)

Presentation Language: Japanese
Presentation Material: English

    Abstract: Detail

The weather forecast model is known to be sensitive to the initial conditions because of chaos. Therefore, it is important to estimate accurately the initial conditions for the weather forecast. Data assimilation is a statistical approach to estimate the most optimal state using both model simulation and observation data. The ensemble Kalman filter (EnKF) is one of advanced data assimilation methods. Covariance localization plays an essential role with a limited ensemble size. Localization limits the influence of observations and reduces the impact of sampling errors. In this study, we increase the ensemble size up to 10240, much larger than the typical choice of about 100, and remove the localization completely on EnKF. We will present the results of 10240-member data assimilation experiments and some problems about the large ensemble data assimilation.