HAR.S.H. Project
SIMILARITY SEARCH IN LARGE-SCALE TIME SERIES COLLECTIONS WITH HARDWARE AWARENESS / HARDWARE-AWARE EXTREME SCALE SIMILARITY SEARCH
The Project
HAR.S.H aims to address major challenges in the large-scale processing of time series collections derived from real-world applications. Large-scale time series data collections are now present in nearly every scientific and societal domain. HAR.S.H will design and implement an extensive suite of algorithms, data structures, and mechanisms to tackle the scalability problem in analyzing vast volumes of time series data, leveraging modern and emerging hardware technologies. The algorithms, data structures, and mechanisms developed will form a robust library, ensuring their easy and efficient use across a wide range of applications. Specifically, HAR.S.H aims to:
Design and develop a new generation of algorithms and data structures that enable efficient parallel and distributed similarity search on large time series collections.
Leverage modern hardware technologies by studying their impact on the performance and scalability of such software.
Enable analysis of multimodal data—including text, images, and video—through integrations using deep learning models.
Latest News
Slides Presented at Researcher's Night
HAR.S.H. related presentation given to attending students in primary and secondary education.
Poster Presented at CSD Reunion
Computer Science Department - University of Crete, Classes of '85/'95/'05 reunion.
Poster Presented at VLDB 2025
"The LAW theorem: Local Reads and Linearizable Asynchronous Replication"
Paper Presented at VLDB 2025
"The LAW theorem: Local Reads and Linearizable Asynchronous Replication"
Similarity Search in Large-Scale Time Series Collections with Hardware Awareness
HARSH: Hardware-Aware extReme-scale Similarity search
- Project Code: ΥΠ3ΤΑ-0560901
- Project Start Date: April 15, 2025
- Project End Date: June 30, 2026
- Funding Body: Ministry of Education, Religious Affairs and Sports, Greece 2.0, National Recovery and Resilience Plan
- Host Institution: University of Crete (UoC), Department of Computer Science
