Demo Data from SIGIR 2026 / reviewers in the wild / expert
Akiharu Sakata
dblp:37/6363
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 1989
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3
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
2 papers |
Hardware accelerators and domain-specific architectures · 65% Processor architecture and microarchitecture · 35% | |
| Databases, data mining, and information retrieval
1 paper |
Database system architecture and tuning · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures › database accelerator
database machine |
0.0 | 2 | 1988 | Accelerating Nonnumerical Processing by an Extended Vector Processor · ICDE 1988 A Relational Database System Architecture Based on a Vector Processing Method · ICDE 1987 |
Processor architecture and microarchitecture
vector processor |
0.0 | 1 | 1988 | Accelerating Nonnumerical Processing by an Extended Vector Processor · ICDE 1988 |
Methods — techniques the papers use, named apart from their topics
vectorization · 0.0pipelined vector processing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1989 | A relational database system architecture based on a vector-processing method
Shun'ichi Torii, Keiji Kojima, Seiichi Yoshizumi, Akiharu Sakata, Yoshifumi Takamoto, Shun Kawabe, Masami Takahashi |
Inf. Sci. | 4 |
| 1988 | Accelerating Nonnumerical Processing by an Extended Vector ProcessorabstractThe problems of utilizing an extended vector processor called IDP (Integrated Database Processor) for nonnumerical processing are discussed. IDP has highly pipelined merge and search vector facilities in addition to conventional vector facilities. This extended vector processor can be utilized not only for primitive relational operations but also for the following applications: (1) complex relational query using multiple indexes; (2) multiway merge/sort utility, and (3) generation and test processing. Vectorization methods and performance improvements are described and analyzed.> Shun'ichi Torii, Keiji Kojima, Yasusi Kanada, Akiharu Sakata, Seiichi Yoshizumi, Masami Takahashi |
ICDE | 4 |
| 1987 | A Relational Database System Architecture Based on a Vector Processing MethodabstractA new relational database system architecture based on a vector processing method is presented. The similarity between table and vector structures was studied. This similarity implies that vector processors have high potential for the improvement of Relational Data Base Management System (RDBMS) performance. In commercial RDBMSs, however, data records are internally organized in complex pointer structures, to which vector processing is not directly applicable. We propose a new vectorization method by which data in the pointer structures are dynamically rearranged into vector form, and collectively processed using a pipelined vector processor. A new pipelined vector processor called an Integrated Database Processor (IDP) which is particularly suitable for our vectorization strategy was developed. IDP is designed as an optional hardware for a general purpose computer. The vectorization method and IDP are applied to Hitachi's new, recently-announced, commercial RDBMS (called RDB1/IDP). In this paper, the vectorization method and the architecture of IDP are described. The performance improvement is also described and analyzed. Shun'ichi Torii, Keiji Kojima, Seiichi Yoshizumi, Akiharu Sakata, Yoshifumi Takamoto, Shun Kawabe, Masami Takahashi, Tsuguo Ishizuka |
ICDE | 4 |