| Project/Area Number |
24650019
|
|---|
| Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Computer system/Network
|
|---|
| Research Institution | The University of Tokyo |
|---|
Principal Investigator |
FUJITA Masahiro 東京大学, 学内共同利用施設等, 教授 (70323524)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
MATSUMOTO Takeshi 東京大学, 大規模集積システム設計教育研究センター, 助教 (40536140)
|
|---|
| Project Period (FY) |
2012-04-01 – 2014-03-31
|
| Project Status |
Completed (Fiscal Year 2013)
|
| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2013: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2012: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
|---|
| Keywords | ストリーム処理 / 設計自動修復 / 高性能計算 / 多重表引 / メモリベース計算 / 自動設計修復 / ハイパフォーマンスコンピューティング / ストリーム処理化 / デバッグ支援技術 |
|---|
| Research Abstract |
In big data analysis, such as analyzing data on images, web manipulations, and sensor networks, same operations are repeated on each data item. Such big data are arranged as very long flows of data, called data stream, so that operations on different data items can be processed in parallel as highly pipelined operations. We have developed a new methodology where such data steams are processed by multiple retrievals of relatively small tables. As all tables are retrieved in parallel, we can expect huge parallelisms. It is also called memory-based computing in contrast to processor-based processing which is widely used today. We have developed a set of techniques by which the processing system can be automatically corrected even if some of the tables are disorder by adjusting other tables appropriately.
|
