Relaxed Queues and Stacks from Read/Write Operations

Considering asynchronous shared memory systems in which any number of processes may crash, this work identifies and formally defines relaxations of queues and stacks that can be non-blocking or wait-free while being implemented using only read/write operations. Set-linearizability and Interval-linearizability are used to specify the relaxations formally, and precisely identify the subset of executions which preserve the original sequential behavior. The relaxations allow for an item to be returned more than once by different operations, but only in case of concurrency; we call such a property multiplicity. The stack implementation is wait-free, while the queue implementation is non-blocking. Interval-linearizability is used to describe a queue with multiplicity, with the additional relaxation that a dequeue operation can return weak-empty, which means that the queue might be empty. We present a read/write wait-free interval-linearizable algorithm of a concurrent queue. As far as we know, this work is the first that provides formalizations of the notions of multiplicity and weak-emptiness, which can be implemented on top of read/write registers only

Contributions to Desktop Grid Computing : From High Throughput Computing to Data-Intensive Sciences on Hybrid Distributed Computing Infrastructures

Since the mid 90’s, Desktop Grid Computing - i.e the idea of using a large number of remote PCs distributed on the Internet to execute large parallel applications - has proved to be an efficient paradigm to provide a large computational power at the fraction of the cost of a dedicated computing infrastructure.This document presents my contributions over the last decade to broaden the scope of Desktop Grid Computing. My research has followed three different directions. The first direction has established new methods to observe and characterize Desktop Grid resources and developed experimental platforms to test and validate our approach in conditions close to reality. The second line of research has focused on integrating Desk- top Grids in e-science Grid infrastructure (e.g. EGI), which requires to address many challenges such as security, scheduling, quality of service, and more. The third direction has investigated how to support large-scale data management and data intensive applica- tions on such infrastructures, including support for the new and emerging data-oriented programming models.This manuscript not only reports on the scientific achievements and the technologies developed to support our objectives, but also on the international collaborations and projects I have been involved in, as well as the scientific mentoring which motivates my candidature for the Habilitation `a Diriger les Recherches

Bridging a Gap Between Research and Production: Contributions to Scheduling and Simulation

Large scale distributed computing infrastructures (e.g., data centers, grids, or clouds) are used by scientists from various domains to produce outstanding research results, such as the discovery of the Higgs Boson in High Energy Physics. These infrastructures are also studied by Computer Scientists to produce their own set of scientific results. Ideally, a virtuous circle should exist between Domain and Computer Scientists: the former raising challenges that could be addressed by the latter. Unfortunately, in many occasions, a gap exists that prevents such an ideal and fostering collaboration. This habilitation covers research works conducted in the fields of scheduling and simulation that contribute to the filling of this gap. It discusses the necessary conditions to achieve this goal and details concrete initiatives in this endeavor

Efficient Learning Machines

Computer scienc

Bioinformatics

This book is divided into different research areas relevant in Bioinformatics such as biological networks, next generation sequencing, high performance computing, molecular modeling, structural bioinformatics, molecular modeling and intelligent data analysis. Each book section introduces the basic concepts and then explains its application to problems of great relevance, so both novice and expert readers can benefit from the information and research works presented here

筑波大学計算科学研究センター 平成24年度 年次報告書

1 平成23年度 重点施策・改善目標　……　22 平成24年度 実施報告　……　53 各研究部門の報告　……　11Ⅰ.素粒子物理研究部門　……　11Ⅱ.宇宙・原子核物理研究部門　……　40 Ⅱ-1.宇宙分野　……　40 Ⅱ-2.原子核分野　……　65Ⅲ.量子物性研究部門　……　88Ⅳ.生命科学研究部門　……　115 Ⅳ-1.生命機能情報分野　……　115 Ⅳ-2.分子進化分野　……　125Ⅴ.地球環境研究部門　……　136Ⅵ.高性能計算システム研究部門　……　146Ⅶ.計算情報学研究部門　……　165 Ⅶ-1.データ基盤分野　……　165 Ⅶ-2.計算メディア分野　……　17

筑波大学計算科学研究センター 平成25年度 年次報告書

1 平成25 年度重点施策および改善目標の達成状況 ...... 22 自己評価と課題 ...... 83 各研究部門の報告 ...... 10I. 素粒子物理研究部門 ...... 10II. 宇宙・原子核物理研究部門 ...... 32II-1. 宇宙物理理論グループ ...... 32II-2. 原子核分野 ...... 56III. 量子物性研究部門 ...... 69IV. 生命科学研究部門 ...... 83IV-1. 生命機能情報分野 ...... 83IV-2. 分子進化分野 ...... 93V. 地球環境研究部門 ....... 104VI. 高性能計算システム研究部門 ...... 118VII. 計算情報学研究部門 ...... 148VII-1. データ基盤分野 ...... 148VII-2. 計算メディア分野 ...... 16

筑波大学計算科学研究センター 平成28年度 年次報告書

まえがき　……　21 センター組織と構成員　……　32 平成 28 年度の活動状況　……　73 各研究部門の報告　……　10I. 素粒子物理研究部門　……　10II. 宇宙物理研究部門　……　36III. 原子核物理研究部門　……　64IV. 量子物性研究部門　……　88V. 生命科学研究部門　……　106 V-1. 生命機能情報分野　……　106 V-2. 分子進化分野　……　122VI. 地球環境研究部門　……　140VII. 高性能計算システム研究部門　……　154VIII. 計算情報学研究部門　……　205 Ⅷ-1. データ基盤分野　……　205 Ⅷ-2. 計算メディア分野　……　22