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Hiroaki Yamanaka

Publications and source records attributed to Hiroaki Yamanaka.

3 recordsLinked to original sources

AiSAQ-in-Filtering for DRAM-free Filtered Information Retrieval

Filtering search is one of the crucial applications of approximate nearest neighbor search (ANNS). In filtering search, label information is used in conjunction with unstructured vector data. ANNS provides efficient similarity search in large-scale datasets, however, the memory footprint of storing both vector data and their associated label becomes a significant cost factor as dataset sizes grow. To address this problem of increasing DRAM usage, we propose AiSAQ-in-Filtering, with a novel quantization method called LiPQ (Label-inclusive Product Quantization). LiPQ combines unstructured data and structured labels into a single representation, leading no growth of encoded data. Our proposal increased recall@1 of single-label searches by up to 55% and fewer disk I/Os compared with existing methods. This also retains the main advantages of AiSAQ, which can reduce DRAM footprint by up to 1/78 and index switching time comparing with existing methods. This proposal can also be applied to sparse-dense hybrid search beyond label filtering such as semantic and keyword search of documents.

cs.IR↗

Revolutionizing Long-Term Memory in AI: New Horizons with High-Capacity and High-Speed Storage

Driven by our mission of "uplifting the world with memory," this paper explores the design concept of "memory" that is essential for achieving artificial superintelligence (ASI). Rather than proposing novel methods, we focus on several alternative approaches whose potential benefits are widely imaginable, yet have remained largely unexplored. The currently dominant paradigm, which can be termed "extract then store," involves extracting information judged to be useful from experiences and saving only the extracted content. However, this approach inherently risks the loss of information, as some valuable knowledge particularly for different tasks may be discarded in the extraction process. In contrast, we emphasize the "store then on-demand extract" approach, which seeks to retain raw experiences and flexibly apply them to various tasks as needed, thus avoiding such information loss. In addition, we highlight two further approaches: discovering deeper insights from large collections of probabilistic experiences, and improving experience collection efficiency by sharing stored experiences. While these approaches seem intuitively effective, our simple experiments demonstrate that this is indeed the case. Finally, we discuss major challenges that have limited investigation into these promising directions and propose research topics to address them.

cs.AI↗

PRAGMA-ENT: Exposing SDN Concepts to Domain Scientists in the Pacific Rim

The Pacific Rim Application and Grid Middleware Assembly (PRAGMA) is an international community of researchers that actively collaborate to address problems and challenges of common interest in eScience. The PRAGMA Experimental Network Testbed (PRAGMA-ENT) was established with the goal of constructing an international software-defined network (SDN) testbed to offer the necessary networking support to the PRAGMA cyberinfrastructure. PRAGMA-ENT is isolated, and PRAGMA researchers have complete freedom to access network resources to develop, experiment, and evaluate new ideas without the concerns of interfering with production networks. In the first phase, PRAGMA-ENT focused on establishing an international L2 backbone. With support from the Florida Lambda Rail (FLR), Internet2, PacificWave, JGN-X, and TWAREN, PRAGMA-ENT backbone connects Open\-Flow-enabled switches at University of Florida (UF), University of California San Diego (UCSD), Nara Institute of Science and Technology (NAIST, Japan), Osaka University (Japan), National Institute of Advanced Industrial Science and Technology (AIST, Japan), and National Center for High-Performance Computing (Taiwan). The second phase of PRAGMA-ENT consisted of evaluation of technologies for the control plane that enables multiple experiments (i.e., OpenFlow controllers) to co-exist. Preliminary experiments with FlowVisor revealed some limitations leading to the development of a new approach, called AutoVFlow. This paper will share our experience in the establishment of PRAGMA-ENT backbone (with international L2 links), its current status, and control plane plans. Discussion on preliminary application ideas, including optimization of routing control; multipath routing control; and remote visualization will also be discussed.

cs.NI↗