Demo Data from EDBT 2026 / reviewers in the wild / expert
Takumi Nito
dblp:164/5512
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Graph data management · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › flash and SSD
data allocation |
0.3 | 1 | 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash Memory · IEEE Trans. Computers 2018 |
Storage systems
flash and SSD |
0.3 | 1 | 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash Memory · IEEE Trans. Computers 2018 |
Storage systems › flash and SSD › flash memory management
garbage collection |
0.3 | 1 | 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash Memory · IEEE Trans. Computers 2018 |
Storage systems › flash and SSD › flash memory
NAND flash |
0.3 | 1 | 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash Memory · IEEE Trans. Computers 2018 |
Graph data management › graph analytics
large-scale graph analytics |
0.1 | 1 | 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash Memory · IEEE Trans. Computers 2018 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Efficient Data-Allocation Scheme for Eliminating Garbage Collection During Analysis of Big Graphs Stored in NAND Flash MemoryabstractA new control scheme for eliminating garbage collection during high-speed analysis of big-graph data stored in NAND flash memory is proposed and evaluated. During big-graph analysis, intermediate results of the analysis are stored in NAND flash memory and updated repeatedly. Under a conventional control scheme, excessive data copying, called “garbage collection,” occurs because overwriting data to NAND flash memory is prohibited. Such excessive data copying degrades performance of big-graph analysis. In contrast, under the proposed control scheme, the controller of NAND flash memory writes the intermediate results, which are updated at the same time, to the same block of NAND flash memory, and the excessive data copying is eliminated completely because all the data in the block can be erased at the same time before the intermediate results are updated. As a result, the proposed scheme shortens analysis time by 88 percent and increases analysis speed for big graphs 8.7 times. The proposed scheme can be applied to three-dimensional NAND flash memory and increases analysis speed 9.5 times. Also, the proposed scheme can be applied to an emerging high-density memory such as three-dimensional vertical chain-cell phase-change memory. These results show that the proposed control scheme enables high-speed analysis of big graphs. Hiroshi Uchigaito, Seiji Miura, Takumi Nito |
IEEE Trans. Computers | 3 |
| 2015 | A control scheme for eliminating garbage collection during highspeed analysis of big-graph data stored in NAND flash memoryabstractA new control scheme for eliminating garbage collection during high-speed analysis of big-graph data stored in NAND flash memory is proposed and evaluated. During big-graph analysis, intermediate results of the analysis stored in NAND flash memory are updated repeatedly. When a conventional control scheme is applied, excessive data copying, called “garbage collection,” occurs because overwriting data to NAND flash memory is prohibited. Such excessive data copying degrades the performance of big-graph analysis. When the proposed control scheme is applied, the controller of NAND flash memory writes the intermediate results which are updated at the same time to the same block of NAND flash memory, and the excessive data copying is eliminated completely because all the data in the block can be erased at the same time before the intermediate results are updated. As a result, the proposed control scheme shortens analysis time by 88% and increases analysis speed for big graphs 8.7 times. These results show that the proposed control scheme enables high-speed analysis of big graphs. Hiroshi Uchigaito, Seiji Miura, Takumi Nito |
ISCAS | 3 |