Efficient and Secure Data Storage for Future Networks: Review and Future Opportunities
AS Alsalim, MA Javed - IEEE Access, 2024 - ieeexplore.ieee.org
With the increase in the number of Internet of Things (IoT) applications, the reliance on
robust networking, reliable communications, and efficient and secure data storage is …
robust networking, reliable communications, and efficient and secure data storage is …
Scalable Billion-point Approximate Nearest Neighbor Search Using {SmartSSDs}
Approximate nearest neighbor search (ANNS) in high-dimensional vector spaces has
become increasingly crucial in database and machine learning applications. Most previous …
become increasingly crucial in database and machine learning applications. Most previous …
A Brief Survey of Vector Databases
X Xie, H Liu, W Hou, H Huang - 2023 9th International …, 2023 - ieeexplore.ieee.org
The explosive growth of massive high-dimensional data requires capabilities for data
processing, storing, and analyzing. This brings significant challenges to traditional …
processing, storing, and analyzing. This brings significant challenges to traditional …
DF-GAS: a Distributed FPGA-as-a-Service Architecture towards Billion-Scale Graph-based Approximate Nearest Neighbor Search
Embedding retrieval is a crucial task for recommendation systems. Graph-based
approximate nearest neighbor search (GANNS) is the most commonly used method for …
approximate nearest neighbor search (GANNS) is the most commonly used method for …
NDSEARCH: Accelerating graph-traversal-based approximate nearest neighbor search through near data processing
Approximate nearest neighbor search (ANNS) is a key retrieval technique for vector
database and many data center applications, such as person re-identification and …
database and many data center applications, such as person re-identification and …
SmartGraph: A Framework for Graph Processing in Computational Storage
Graph processing plays a pivotal role in numerous large-scale applications, including social
and transportation networks. One of the primary challenges in handling large-scale graph …
and transportation networks. One of the primary challenges in handling large-scale graph …
In-Storage Acceleration of Graph-Traversal-Based Approximate Nearest Neighbor Search
Approximate nearest neighbor search (ANNS) is a key retrieval technique for vector
database and many data center applications, such as person re-identification and …
database and many data center applications, such as person re-identification and …
Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics
The ability to perform machine learning (ML) tasks in a database management system
(DBMS) is a new paradigm for conventional database systems as it enables advanced data …
(DBMS) is a new paradigm for conventional database systems as it enables advanced data …
Accelerating Graph-based Vector Search via Delayed-Synchronization Traversal
Vector search systems are indispensable in large language model (LLM) serving, search
engines, and recommender systems, where minimizing online search latency is essential …
engines, and recommender systems, where minimizing online search latency is essential …
An Energy-Efficient In-Memory Accelerator for Graph Construction and Updating
Graph is widely utilized as a key data structure in many applications, such as social network
and recommendation systems. However, many real-world graphs are constructed with large …
and recommendation systems. However, many real-world graphs are constructed with large …