The global ocean economy is growing. In Nova Scotia alone, ocean-related activity generates $5 billion in revenue and 14% of provincial employment with ocean industries and university-based expertise thriving, and this is set to double in the next 15 years. Data is everywhere. The analysis of this data is what should be driving business growth. Canadian industry struggles to capture its global share of the ocean opportunity without data-driven insight to integrate and leverage new technologies, and make better-informed business decisions - an issue DeepSense is built to tackle.
- A platform for industry to do applied R&D in analytics and the ocean economy with university experts, graduate students, postdocs and applied research scientists, and professional software engineers in a very cost-effective setting.
- An innovation environment that brings together industry with data and ocean scientists to develop commercially-useful predictive models, analytical prototypes, and applications for use in the blue economy.
- An engine to help accelerate the development of a new industry sector focused on the creation of ocean data products, computational models, and analytical applications.
A collaborative model/process for supporting ground-breaking applied industry/university projects, drawing on ocean science, data science and analytics, to accelerate the safe and sustainable development of the blue economy in areas including fisheries & aquaculture, seaport & logistics, and security & defense.
- Computer Science and Software Engineering
- Marine/Ocean Sciences
- Defense and Security Industries
- Fisheries and Aquaculture
- Ocean Industries
Industry Liaison Officer
Equipment 5 piece(s)
Act as the public interface for users to interact with the cluster. Users organize their data and submit jobs to compute nodes from login nodes.
Run users' computations that needs large memories.
Totally 20 machines in this cagetory. They have 512GB of memory and 20 cores each with 100GbE network connection.
Provide as much as 1T of memory for users' computations that consume huge memories.
Totally 4 machines in this cagetory. They have 1TB of memory and 20 cores each with 100GbE network connection.
Provide GPU computing facilities to researchers.
Totally 10 machines in this category. They have 512GB of memory, 2XP100 GPU modules, and 20 CPU cores each with 100GbE network connection.
Date submitted: Tue, Jun 4, 2019 10:03 AM
Date updated: Tue, Jun 4, 2019 10:15 AM