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R-CCS Cafe

R-CCS Cafe (formerly AICS Cafe) is a place where the researchers in R-CCS 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 R-CCS .

  • 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: Lecture Hall (6th floor) at R-CCS
  • Language : 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 141st AICS Cafe
Date and Time: Fri. July 20, 2018, 15:30-16:30
Place: Lecture Hall (6th floor) at AICS

Title: Computing Matrix Functions on the K Computer
Speaker: William Dawson (Riken-CCS Computational Molecular Science Research Team)

Presentation Language: English
Presentation Material: English

Abstract:

In this talk, I will present a new library for computing matrix functions, and will do my best to present it in a way that should be of interest to researchers from R-CCS’s many disciplines. Matrix functions have a number of applications including materials science, the solution of partial differential equations, and the study of real world networks. In this talk, I will review the theory of matrix functions, and discuss several methods of computation. Then I will present the parallelization strategy of our library, including the use of communication avoiding algorithms and task based parallelization. I will discuss usability considerations, including how to build a library in Fortran which can be called from many different programming languages. I will finish by presenting a number of different applications of this library, including quantum chemistry, social network analysis, search engine optimization, and the calculation of the eigendecomposition of a matrix.

The 140th AICS Cafe
Date and Time: Fri. July 6, 2018
Place: Lecture Hall (6th floor) at AICS

Title: TBD
Speaker: TBD

Abstract:

TBD

The 139th R-CCS Cafe-part Ⅱ
Date and Time: Thu. May 31, 2018, 14:30 – 16:00
Place: Lecture Hall (6th floor) at R-CCS

Title: ABC of Active Listening
Speaker: Toda(Clinical Psychologist)

Presentation Language: Japanese
Presentation Material: Japanese

The 139th R-CCS Cafe-part Ⅰ
Date and Time: Thu. May 31, 2018, 13:00 – 14:00
(14:00 – 14:30    Cafe Time)
Place: Lecture Hall (6th floor) at R-CCS

Title: Reproducibility and accuracy of BLAS routines and their application
Speaker: Roman Iakymchuk(Postdoctoral researcher, KTH, Sweden)

Presentation Language: English
Presentation Material: English

Abstract: Detail

On modern multi-core, many-core, and heterogeneous architectures, floating-point computations, especially reductions, may become non-deterministic and, therefore, non-reproducible mainly due to the non-associativity of floating-point operations and the dynamic scheduling. We address the problem of reproducibility in the context of fundamental linear algebra operations -- like the ones included in the Basic Linear Algebra Subprograms (BLAS) library -- and propose algorithms that yields both reproducible and accurate results. We extend this approach to the higher level linear algebra algorithms, e.g. the LU factorization, that are built on top of these BLAS kernels. We present these reproducible and accurate algorithms for the BLAS routines and the LU factorization as well as their implementations in parallel environments such as Intel server CPUs, Intel Xeon Phi, and both NVIDIA and AMD GPUs. We show that the performance of our implementations is comparable to the standard ones.

The 138th R-CCS Cafe
Date and Time: Wed. Mar. 30, 2018, 14:00-15:00
Place: Lecture Hall (6th floor) at R-CCS

Title: Introduction to activities of RIKEN Scientists' Assembly ( and Carbon Nanotube-Based Quantum Photonic Devices )

Speaker: Yuichiro Kato (Chief Scientist Laboratories of Nanoscale Quantum Photonics Laboratory, RIKEN Cluster for Pioneering Research (CPR), and Team Leader of Quantum Optoelectronics Research Team, RIKEN Center for Advanced Photonics (RAP))

Presentation Language: Japanese
Presentation Material: English

The 137th R-CCS Cafe(1st meeting as R-CCS Cafe)
Date and Time: Tue. Apr. 24, 2018, 10:00-15:00
Place: Seminar room (1st. floor) at R-CCS

Speaker:
Thomas Schulthess (Swiss CSCS/ETH Director)
Scott Klasky (Senior Scientist ORNL)

Presentation Language: English
Presentation Material: English

Program: Detail

10:00-12:00 Tutorial (Part I)
13:00-13:50 Tutorial(Part II)

Title:Enhancing Scientific Data Management for Exascale
Speaker:Scott Klasky (Senior Scientist ORNL)
Abstract: As we continue toward exascale, scientific data volume is continuing to scale and becoming more burdensome to manage. In this talk, we lay out opportunities to enhance state of the art data management techniques. We emphasize well principled data compression, and using it to achieve progressive refinement. This can both accelerate I/O and afford the user increased flexibility when she interacts with the data. The formulation naturally maps onto enabling partitioning of the progressively improving-quality representations of a data quantity into different media-type destinations, to keep the highest priority information as close as possible to the computation, and take advantage of deepening memory/storage hierarchies in ways not previously possible. Careful monitoring is requisite to our vision, not only to verify that compression has not eliminated salient features in the data, but also to better understand the performance of massively parallel scientific applications. Increased mathematical rigor would be ideal, to help bring compression on a better-understood theoretical footing, closer to the relevant scientific theory, more aware of constraints imposed by the science, and more tightly error-controlled. Throughout, we highlight pathfinding research we have begun exploring these related topics, and comment toward future work that will be needed.

14:00~15:00 Seminar
Title:Creating ADIOS-2 for scientific exascale data
Speaker:Scott Klasky (Senior Scientist ORNL)
Abstract: What is Scientific Exascale data? For some it is really big data from scientific experiments and simulations. We use it in Data Intensive Science, which is an acknowledgement that as simulations and experiments continue to generate larger amounts of data, we must turn our attention on how to move, store, manage, analyze and visualize this data in a timely fashion. We are already seeing Petascale simulations produce close to 100 PB per simulation, and we are hearing simulations for Exascale computing trying to approach 100 EB of data per week. Clearly the cost of “write once read never” is becoming too expensive and we must start to create software eco-systems to help us cope with this flood of data from scientific instruments and calculations. We have built the idea of I/O staging in the Adaptable I/O system (ADIOS) to ingest, reduce, and move data on HPC systems and over the WAN to other computational resources, and my talk focuses on creating a software ecosystem which employs these techniques to cope with the extreme amounts of data being produced in the DOE. Furthermore, Exascale data must be re-purposed in time in order to validate the results against physics experiments, such as the ITER fusion tokamak. This creates new challenges which must be explored and developed into an overarching infrastructure for scientific data. Our goal is to create an I/O framework that addresses most of the use-cases arising from both the Exascale challenges and the new scientific instruments coming on-line in the next 10 years.

15:00~16:00 Seminar
Title:Reflecting on the goal and baseline for exascale computing
Speaker:Thomas Schulthess (Swiss CSCS/ETH Director)
Abstract: Application performance is given much emphasis in discussions of exascale computing. A 50-fold increase in sustained performance over today’s applications running on multi-petaflops supercomputing platforms should be the expected target for exascale systems deployed early next decade. In the present talk, we will reflect on what this means in practice and how much these exascale systems will advance the state of the art. Experience with today’s platforms show that there can be an order of magnitude difference in performance within a given class of numerical methods, depending only on choice of architecture and implementation. This bears the questions on what our baseline is, over which the performance improvements of exascale systems will be measured. Furthermore, how close will these exascale systems bring us to deliver on scientific goals, such as convection resolving global climate simulations or throughput oriented computations for meteorology?

The 136th AICS Cafe(Special meeting 4)
Date and Time: Tue. Mar. 20, 2018, 16:00-17:00
Place: Lecture Hall (6th floor) at AICS

Title: Simulating quantum mechanics on a classical computer
Speaker: Garnet Kin-Lic Chan(California Institute of Technology)

Presentation Language: English
Presentation Material: English

Abstract: Detail

Quantum mechanics is the fundamental theory underlying all of chemistry, materials science, and the biological world, yet solving the equations appears to be an exponentially hard problem. Is there hope to simulate the quantum world using classical computers? I will discuss why simulating quantum mechanics is not usually as hard as it first appears, and give some examples of how modern day quantum mechanical calculations are changing our understanding of practical chemistry and materials science.

The 135th AICS Cafe
Date and Time: Wed. Mar. 14, 2018, 15:30-16:30
Place: Lecture Hall (6th floor) at AICS

Title: Towards a science of high performance design
Speaker: Tze Meng Low(Assistant Research Professor, Carnegie Mellon University, USA)

Presentation Language: English
Presentation Material: English

Abstract: Detail

Applications are becoming more varied. Architectures are becoming more complex. Yet software implemented by the expert still achieves higher performance than most automatically generated code despite two decades of research in automatic empirical optimization systems. Can we ever get expert-level performance automatically? In this talk, I will discuss how expert-level performance in the dense linear algebra domain can be systematically attained through the use of formal methods and analytical models. Specifically, I will present our analytical models and their underlying hardware principles. I will demonstrate how these analytical models are resilient against changes. I will also share how analytical models from the dense linear algebra domain have been adapted to design high performance implementations for problems in other domains.

The 134th AICS Cafe(Special meeting 3)
Date and Time: Mon. Mar. 12, 2018, 15:00-16:00
Place: Lecture Hall (6th floor) at AICS

Title: Deep learning applications and company structure behind it
Speaker: Shohei Hido(Preferred Networks, Inc.)

Presentation Language: Japanese
Presentation Material: Japanese

Abstract: Detail

Preferred Networks works on R&D for deep learning applications in many industries. In this talk, deep learning basics, recent results by PFN, and internal support and structure behind it will be presented.

The 133rd AICS Cafe-part Ⅱ
Date and Time: Tue. Mar. 6, 2018, 14:30 – 16:30 (partⅠandⅡ)
Place: Lecture Hall (6th floor) at AICS

Title: Enabling Exascale Fluid Dynamics: Adaptive Mesh Refinement Speaker: Philipp Schlatter (KTH Stockholm)

Presentation Language: English Presentation Material: English

    Abstract: Detail
The complex nature of turbulent fluid flows implies that the computational resources needed to accurately model problems of industrial and academic relevance is virtually unbounded. Computational Fluid Dynamics (CFD) is therefore a natural driver for exascale computing and has the potential for substantial societal impact, like reduced energy consumption, alternative sources of energy, improved health care, and improved climate models. Extreme-scale CFD poses several cross disciplinary challenges e.g. algorithmic issues in scalable solver design, handling of extreme sized data with compression and in-situ analysis, resilience and energy awareness in both hardware and algorithm design. The wide range of topics makes exascale CFD relevant to a wider HPC audience, extending outside the traditional fluid dynamics community. This talk will summarise the work within the EU funded Horizon 2020 project ExaFLOW, which brings together leading CFD experts and users from both industry and academica: Partners include KTH Royal Institute of Technology (Sweden), Imperial College (UK), University of Southampton (UK), University of Edinburgh (UK), University of Stuttgart (Germany), and industrial partners McLaren (UK) and ACSC (Germany). Special focus is on adaptive mesh refinement (AMR), which is identified as one of the key aspects of large-scale, exascale simulations in CFD: The solution of such problems is a-priori unknown, such that the mesh structure necessarily needs to be solution-dependent, and adjust during the progress of a simulation. In this talk we focus on AMR implemented in Nek5000, a code aimed at direct numerical simulations, based on the spectral element method (SEM). The two main ingredients for AMR are tools for automatic mesh refinement and error estimators which allow for optimal error control. New capabilities in Nek5000 enable the use of the h-refinement method for mesh adaptation, where selected elements are split via quadtree (2D) or octree (3D) structures. Two methods are considred for estimating the error. The first method is local and based on the spectral properties of the solution on each element. These so-called spectral error indicators come with a low overhead and are easily implemented but they provide only a local measure of the error. The second method, on the other hand, is goal-oriented and takes into account both the local properties of the solution and the global dependence of the error in a functional of interest (such as drag or lift) via the resolution of an adjoint problem. These so-called adjoint error estimators are based on a similar work done within the framework of the finite element method. AMR capabilities are demonstrated in Nek5000 and applied to simple steady and unsteady test cases, such as the flow past a cylinder and the lid-driven cavity, in two and three dimensions. The definition and implementation of both error estimation methods are presented and discussed. The results obtained with both methods are compared and are shown to efficiently reduce the number of degrees of freedom required to reach a given tolerance on the solution compared to conforming refinement. Moreover, the gains in terms of mesh generation, accuracy and computational cost are discussed by analyzing the convergence of some functional of interest and the evolution of the mesh as refinement proceeds.