- 担当教員
- 宮﨑 純
- 使用教室
- 月7-8(W833)
- 単位数
- 講義：2 演習：0 実験：0
- 講義コード
- 76061
- シラバス更新日
- 2015年3月24日
- 講義資料更新日
- 2015年3月16日
- 学期
- 前期
講義概要
The amount of information which can be handled by computers is drastically increasing. The information affects trend analyses of the economy and scientific research areas, e.g., biology and physics, as well as Web search engines. Since it is currently a big issue that we can efficiently manage and utilize such a large amount of data, solving this is expected to lead to an effective use of the data. Therefore, many studies have been conducted to deal with this issue by using the parallel computer systems with modern high performance hardware.
In this course, we learn new concepts and technologies on parallel computation for managing and processing a large amount of data.
講義の目的
The objective of this course is to learn the concepts, computation models, and techniques for new parallel computing. We mainly focus on the new computer systems with modern high performance hardware from two aspects: cloud computing from a macro viewpoint and data management for manycore processors from a micro viewpoint.
講義計画
1. Introduction
2. Key-value store, data model
3. Consistency models for cloud data store
4. MapReduce framework
5. Text processing with MapReduce
6. Graph algorithms for MapReduce
7. Memory hierarchy and high performance computing
8. Cache-conscious data placement
9. Cache-conscious search algorithms
10. Atomic operation, synchronization
11. Lock-free algorithms (1)
12. Lock-free algorithms (2)
13. Software transactional memory
14. Hardware transactional memory
15. Advanced topics
教科書・参考書等
Reference books:
1. J. Lin, C. Dyer, "Data-Intensive Text Processing with MapReduce", Morgan & Claypool Publisher, 2010
2. T. Harris, J. Larus, R. Rajwar, "Transactional Memory", 2nd edition, Morgan & Claypool Publisher, 2010
関連科目・履修の条件等
Related Courses: Advanced Computer Architectures, Advanced Data Engineering, Concurrent System Theory
成績評価
Assignments (40%) and Term exam (60%)
