| Paper Abstract and Keywords |
| Presentation |
2026-01-28 09:30
[Invited Talk]
Kioxia AiSAQ
-- SSD-intensive Large-Scale Information Retrieval for Generative AI -- Kento Tatsuno (KIOXIA) VLD2025-71 RECONF2025-122 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
This talk introduces KIOXIA AiSAQ, a technology that searches for information from data stored on SSDs. The development of generative AI, such as Large Language Models (LLMs), crucially requires massive amounts of data. The RAG (Retrieval Augmented Generation) approach – which involves LLMs accessing and utilizing data from external memories in addition to the knowledge they’ve learned themselves – is receiving significant attention. Conversely, the volume of data in the world is constantly increasing, making the use of SSDs and other storage solutions suitable for large memory capacities optimal. Through KIOXIA AiSAQ, as we propose, we can build generative AI systems that search and utilize large-scale data on SSDs. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
KIOXIA AiSAQ / SSD / Generative AI / RAG / Vector Search / Approximate Nearest Neighbor Search / / |
| Reference Info. |
IEICE Tech. Rep., vol. 125, no. 342, RECONF2025-122, pp. 23-27, Jan. 2026. |
| Paper # |
RECONF2025-122 |
| Date of Issue |
2026-01-20 (VLD, RECONF) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
VLD2025-71 RECONF2025-122 |
| Conference Information |
| Committee |
RECONF VLD |
| Conference Date |
2026-01-27 - 2026-01-28 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
FPGA Applications, etc. |
| Paper Information |
| Registration To |
RECONF |
| Conference Code |
2026-01-RECONF-VLD |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Kioxia AiSAQ |
| Sub Title (in English) |
SSD-intensive Large-Scale Information Retrieval for Generative AI |
| Keyword(1) |
KIOXIA AiSAQ |
| Keyword(2) |
SSD |
| Keyword(3) |
Generative AI |
| Keyword(4) |
RAG |
| Keyword(5) |
Vector Search |
| Keyword(6) |
Approximate Nearest Neighbor Search |
| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Kento Tatsuno |
| 1st Author's Affiliation |
KIOXIA Corporation (KIOXIA) |
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| Speaker |
Author-1 |
| Date Time |
2026-01-28 09:30:00 |
| Presentation Time |
40 minutes |
| Registration for |
RECONF |
| Paper # |
VLD2025-71, RECONF2025-122 |
| Volume (vol) |
vol.125 |
| Number (no) |
no.341(VLD), no.342(RECONF) |
| Page |
pp.23-27 |
| #Pages |
5 |
| Date of Issue |
2026-01-20 (VLD, RECONF) |