理化学研究所 計算科学研究センター

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R-CCS Cafe

R-CCS Cafe は、異分野融合のための足掛かりとして、計算科学研究センター(R-CCS)に集う研究者が井戸端会議的にざっくばらんに議論する場として、毎月2回程度予定しております。興味をお持ちの方は原則どなたでも参加可能です。

  • 目 的: 異分野間の壁を超えた研究協力を促進し、新しい学問分野の開拓を目指すため、 研究者間の情報交換・相互理解の場を提供し、研究協力のきっかけを作る。
  • 会 場:R-CCS 6階講堂(予定)
  • 言 語:講演は日本語/英語、スライドは英語
  • その他:講演者は他分野の方にも理解できる発表を心掛け、参加者は積極的に質問しましょう。

「AICS Cafe」は2018年度より「R-CCS Cafe」に名称が変わりました。


第166回 第1部
日時: 2019年3月25日(月)、15:00 - 16:00
場所: R-CCS 1階セミナー室

・講演題目:米国における気候数値モデルの開発状況報告
・講演者:吉田 龍二 (Unversity of Colorado Boulder, CIRES/NOAA ESRL)
※発表は日本語、スライドは英語

講演要旨:

米国における気候数値モデル開発の一例をご紹介いたします。発表者は米国エネルギー省SciDACプロジェクトを通してE3SMという全球モデル開発に参加しています。E3SMはエネルギー問題を解決するために,高解像度の地球環境シミュレーションを実施し、水循環,雪氷-海洋系,そして生物圏の理解を進めることを目的に開発されているモデルです。計算能力向上のために,機械学習やGPUコンピューティングにも力を入れており、米国エネルギー省の次世代スーパーコンピュータ「Shasta」で計算が実行される予定です。この次世代機はクレイ社によって発表されたばかりで,AMD,Intel,ARM,そしてGPUといった様々な計算コアが実装される予定です。モデル開発者は,まだ見ぬ次世代機に適用するため様々な手法を考えています。

第166回 第2部
日時: 2019年3月25日(月)、16:00 - 17:00
場所: R-CCS 1階セミナー室

・講演題目:Agent-based model (ABM) for city-scale traffic simulation: a case study on San Francisco.
・講演者:Bingyu Zhao, University of California at Berkeley
※発表・スライド共に英語

講演要旨:

Agent-Based Model (ABM) is a promising tool for city-scale traffic simulation to understand the complex behaviour of the entire urban transportation system under different scenarios. In the ABM, traffic is intuitively simulated as movements and interactions between large numbers of agents, each capable of finding the route for an individual traveller or vehicle. In this talk, the development of such an ABM simulation tool will be presented to reproduce the traffic patterns of the city of San Francisco. The model features a detailed road network and hour-long simulation time step to capture realistic variations in traffic conditions. Agent speed is determined according to a simplified volume-delay macroscopic relationship, which is more efficient than applying microscopic rules (e.g., car following) for evaluating city-scale traffic conditions. Two particular challenges of building such an ABM will be discussed in particular: data availability and computational cost. The key inputs to the ABM are sourced from standard and publicly available datasets, including the travel demand surveys published by local transport authorities and the road network data from the OpenStreetMap. In addition, an efficient priorityqueue based Dijkstra algorithm is implemented to overcome the computational bottleneck of agent routing. The ABM is designed to run on High Performance Computing (HPC) clusters, thereby improving the computational speed significantly. Preliminary validation of the ABM is conducted by comparing its results with a published model. Overall, the ABM has been demonstrated to run efficiently and produce reliable results. Use cases of the ABM tool will be demonstrated through two examples, including evaluating the value of real-time traffic information and assessing the outcomes of complex network-level emission mitigation measures.

第165回(特別版 第3回)
日時: 2019年3月18日(月)、13:30 - 15:00
場所: R-CCS 6階講堂

・講演題目:Extreme Data Management Analysis and Visualization for Exascale Computing and Economic Development
・講演者:Prof. Valerio Pascucci(Director of the Center for Extreme Data Management Analysis and Visualization (CEDMAV) of the University of Utah)
※発表・スライド共に英語

講演要旨: 詳細を見る

Effective use of data management techniques for analysis and visualization of massive scientific data is a crucial ingredient for the success of any supercomputing center and cyberinfrastructure for data-intensive scientific investigation. In the progress towards exascale computing, the data movement challenges have fostered innovation leading to complex streaming workflows that take advantage of any data processing opportunity arising while the data is in motion. This technology finds practical use in a number of industry applications including precision agriculture and tele-medicine. In this talk I will present a number of techniques developed at the Center for Extreme Data Management Analysis and Visualization (CEDMAV) that allow to build a scalable data movement infrastructure for fast I/O while organizing the data in a way that makes it immediately accessible for analytics and visualization. In addition, I will present a topological analytics framework that allows processing data in-situ and achieve massive data reductions while maintaining the ability to explore the full parameter space for feature selection. Overall, this leads to a flexible data streaming workflow that allows working with massive simulation models without compromising the interactive nature of the exploratory process that is characteristic of the most effective data analytics and visualization environment.
※ストリーミング型大規模データ可視化ツールOpenViSUSのチュートリアルを3月20日に行います。
詳細はOpenViSUS ストリーミング型大規模データ可視化チュートリアル(2019年3月20日)をご覧下さい。

第164回(特別版 第2回)
日時: 2019年3月15日(金)、13:15 - 15:00
場所: R-CCS 6階講堂

・講演題目:計算機シミュレーションは科学といえるのか:科学哲学からの視点
・講演者:伊勢田 哲治(京都大学、准教授)
※発表・スライド共に英語

講演要旨: 詳細を見る

科学的研究とそうでないものを分かつものはなんだろうか。この問いへの一つの答えは、経験科学は実験や観察に依拠して理論構築するというものである。では、その見方によれば計算機シミュレーションを用いた「実験」はどう扱われるだろうか。計算機シミュレーションによる研究は科学と言えないのだろうか。計算機シミュレーションは近年は科学哲学においても注目されており、この問いに関わるような考察も行われている。今回の講演ではそうした科学哲学の近年の動きを踏まえながら、計算機シミュレーションの科学における位置づけについて考えていきたい。

第163回 第1部
日時: 2019年3月1日(金)、13:00 - 14:00
場所: R-CCS 6階講堂

・講演題目:Novel features of a familiar theory --- QCD near phase boundary analyzed through large scale numerical simulations
・講演者:青木 保道(連続系場の理論研究チーム チームリーダー)
※発表・スライド共に英語

講演要旨: 詳細を見る

Understanding the chiral symmetry and its spontaneous breakdown is essential to theoretically reveal the nature of QCD (Quantum Chromo Dynamics) in the Standard Model of particle physics. To this end non-perturbative approaches to QCD dynamics are indispensable and numerical computation based on lattice QCD is only one available method to pursue this for targeted precision in the state-of-the-art application. Ever since the first trial in this approach started in 1980, tremendous effort to improve the algorithms has been made. With that and the increased computer capability we (lattice community) now achieved percent level precision computation for not all, but, some important physical quantities. On the other hand, if one's focus is at the boundary of chiral symmetric - broken "phases", then a delicate treatment of the chiral symmetry is required to even predict the qualitative nature of the system. Such a treatment has become possible only recently in large-scale numerical simulations, which have led to some hints of novel features of QCD. Taking the latter examples, this talk describes such features of QCD, which appears in two different contexts: 1) when the numbers of quarks are increased and 2) in the finite temperature phase transition of two-flavor QCD. The implication to the physics beyond the Standard Model 1); and also the impact to the real world 2) are discussed with the results obtained from large scale numerical simulations. Finally problems which needs to be solved in the next generation supercomputers are also discussed.

第163回 第2部
日時: 2019年3月1日(金)、14:00 - 15:00
場所: R-CCS 6階講堂

・講演題目:Next Generation System Software for High Performance Big Data
・講演者:佐藤 賢斗(高性能ビッグデータ研究チーム チームリーダー)
※発表・スライド共に英語

講演要旨: 詳細を見る

The High Performance Big Data Research Team is investigating and developing system software to facilitate extreme-scale big data processing, machine learning and deep learning for the K computer, post-K computer and beyond. The computational power in high performance computing (HPC) systems has been dramatically increasing, driven in particular by advanced multi/many-core architectures and new memory technologies such as high bandwidth memory and hybrid memory cubes. Although these HPC systems are keeping pace with required computational and memory performance for running scientific applications, they are inadequate with respect to I/O performance required by data-intensive applications. In this talk, we briefly introduce various approaches to resolve these I/O issues and future research directions for the next generation HPC systems.

第163回 第3部
日時: 2019年3月1日(金)、15:15 - 16:15
場所: R-CCS 6階講堂

・講演題目:Towards Next Generation HPC Architecture and its Power Management
・講演者:近藤 正章(次世代高性能アーキテクチャ研究チーム チームリーダー)
※発表・スライド共に英語

講演要旨: 詳細を見る

The continuous improvement in processing speed in high-performance computer systems has been enabled by transistor scaling known as Moore's law. However, this trend is predicted to end in the near future. It is vital to research and develop new, more efficient high performance architectures to continue realizing high performance computing systems. One of the missions of our team is to research and develop a next-generation high-performance computer architecture together with strategies to improve the power efficiency of exascale supercomputer systems. Our research focus includes non-von Neumann architectures, integrating next generation non-volatile memories and/or various types of accelerators into a general-purpose processor, acceleration of machine learning computations, and hybrid computing architectures that combine new and classical computing models. In this talk, we briefly introduce our recent research efforts on next generation high-performance architectures. We also present a power-aware resource management framework which have been developed by our JST CREST project. The developed framework controls power allocation among co-scheduled jobs to optimize total system throughput and power-efficiency within a given power constraint. We have tested this framework on a large-scale HPC cluster system with about 1000 compute-nodes and showed that it can successfully manage the system's power consumption.

第162回 (特別版 第1回)
日時: 2019年2月22日(金)、10:40 - 11:40
場所: R-CCS 6階講堂

・講演題目:An Introduction to Quantum Computing and Its Application, Probably
・講演者:Bo Ewald(President, D-WAVE INTERNATIONAL)
※発表・スライド共に英語

講演要旨: 詳細を見る

This presentation will briefly introduce the ideas behind quantum mechanics and its possible application in quantum sensing, communication and computing. We’ll then discuss the ideas and principles that have enabled the world’s first quantum computers. We’ll briefly review the technologies and architectures, then dive a little more deeply into how the D-Wave quantum annealing computer works. We’ll survey the “proto-applications” that customers have been developing in areas of optimization, machine learning and material science that point the way to production use of quantum computers in the next few years. Finally, we’ll discuss some of the future directions of quantum computing.

第161回
日時: 2019年2月15日(金)、15:30 - 16:30
場所: R-CCS 6階講堂

・講演題目:Recent advances in MXenes: From fundamentals to applications
・講演者:Mohammad Khazaei(量子系物質科学研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

The family of MAX phases — with chemical formula of Mn+1AXn, where n = 1, 2, or 3, “M” is an early transition metal (Sc, Ti, Zr, Hf, V, Nb, Ta, Cr, Mo), "A" is A group elements (Al, Si, P, S, Ga, Ge, As, In, Sn) and "X" is carbon and/or nitrogen — are a large family of layered ceramics with structural applications. Recently, MAX phases have been exfoliated into 2D single and/or multi Mn+1Xn layers by using appropriate acid solutions. The resulting 2D-Mn+1Xn transitional metal carbides and nitrides have been named as MXenes. Considering a large number of compositional possibilities of MAX phase compounds, a large number of MXenes with unprecedented properties could also be obtained in the future. Owing to their large surface area, hydrophilicity, adsorption ability, and high surface reactivity, 2D MXenes have experimentally attracted attention for many potential applications, e.g., catalysts, ion batteries, gas storage media, and sensors. Given the fast progress of MXene-based science and technology, in this presentation, I would like to update your knowledge of electronic properties and some of the possible applications of MXenes.

第160回 第1部
日時: 2019年2月1日(金)、13:00 - 14:00
場所: R-CCS 6階講堂

・講演題目:Regional-scale data assimilation with Himawari-8 satellite radiances
・講演者:本田 匠(データ同化研究チーム)
※発表・スライド共に英語

講演要旨: 詳細を見る

In this talk, we review our achievement in regional-scale data assimilation with Himawari-8 satellite radiances. In July 2015, the Japan Meteorological Agency (JMA) started full operations of their new geostationary satellite “Himawari-8”, the first of a series of the third-generation geostationary meteorological satellites. Himawari-8 can produce high-resolution observations with 16 frequency bands every 10 minutes for full disk. To assimilate Himawari-8 radiances, we implemented a radiative transfer model into a regional-scale data assimilation system known as SCALE-LETKF, consists of the Scalable Computing for Advanced Library and Environment-Regional Model (SCALE-RM) and the Local Ensemble Transform Kalman Filter (LETKF). We assimilated all-sky every-10-minute infrared (IR) radiances from Himawari-8. The results showed that assimilating the every-10-minute Himawari-8 IR radiances improves the analyzed tropical cyclone (TC) structure and intensity forecasts. In another case in September 2015, the heavy precipitation forecasts are greatly improved by assimilating the Himawari-8 IR observations. We ran a rainfall-runoff model using the improved precipitation forecasts and found that assimilating the Himawari-8 observations frequently may give longer lead times in terms of the flood risk. We also show other case studies on a different TC case and the extremely-heavy precipitation event in July 2018.