Advanced techniques and examples for materials science
著者
書誌事項
Advanced techniques and examples for materials science
(The art of high performance computing for computational science, v. 2)
Springer, c2019
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book presents advanced and practical techniques for performance optimization for highly parallel processing. Featuring various parallelization techniques in material science, it is a valuable resource for anyone developing software codes for computational sciences such as physics, chemistry, biology, earth sciences, space science, weather, disaster prevention and manufacturing, as well as for anyone using those software codes.Chapter 1 outlines supercomputers and includes a brief explanation of the history of hardware. Chapter 2 presents procedures for performance evaluation, while Chapter 3 describes the set of tuned applications in materials science, nanoscience and nanotechnology, earth science and engineering on the K computer. Introducing the order-N method, based on density functional theory (DFT) calculation, Chapter 4 explains how to extend the applicability of DFT to large-scale systems by reducing the computational complexity. Chapter 5 discusses acceleration and parallelization in classical molecular dynamics simulations, and lastly, Chapter 6 explains techniques for large-scale quantum chemical calculations, including the order-N method.
This is the second of the two volumes that grew out of a series of lectures in the K computer project in Japan. The first volume addresses more basic techniques, and this second volume focuses on advanced and concrete techniques.
目次
Chapter 1: Supercomputers and application performance.- Chapter 2: Performance optimization of applications.- Chapter 3: Case studies of performance optimization of applications.- Chapter 4: O(N) methods.- Chapter 5: Acceleration of Classical Molecular Dynamics Simulations.- Chapter 6: Large scale quantum chemical calculation.
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