Market Proven
AI and Machine Learning
AI and Machine Learning
AI and Machine Learning
Inference and Real-Time Applications need vast amounts of data to learn pattern, train models, and make predictions. Robust storage is essential for efficiently managing and accessing data. Two 10,000 GPUs success cases.
Oil and Gas
AI and Machine Learning
AI and Machine Learning
From sub-surface oil wells to monitor assets, storage system is used to support big data applications to analyze seismic data. High throughput and operation continuity are top solution values to increase drilling and production.
Genomics
AI and Machine Learning
Genomics
Whole Genome Sequencing (WGS) and Whole Exome Sequencing (WES) for diagnostic and research purposes generate a large volume of raw data. A single human genome takes up 100 GB of storage space.
Geographical Mapping
Geographical Mapping
Geographical Mapping
The challenge in creating and processing geospatial data is that raw data needs to be stored in the highest resolution and detail as possible. Datasets are growing very fast, and needed for continuous exploitation and computation.
Satellite Observatory
Geographical Mapping
Geographical Mapping
The demand is high in building more flexibility for the rising capacity of astronomical data. While taking advantage of low-cost data storage, more funds can be used toward observations and discoveries, instead of IT.
Meteorology/Climate
Geographical Mapping
Meteorology/Climate
Predictions of climate and weather are data intensive. Modern predictions require the use of high-performance computing. The amount of data is substantial after data assimilation, simulations, and analysis/reanalysis.
Media and Entertainment
Media and Entertainment
Media and Entertainment
For fast data processing and better content management, petabyte-scale storage is critically required to address the creation, collaborative editing, post-production and transmission of various types of digital formats/assets.
Video Surveillance
Media and Entertainment
Media and Entertainment
Most difficult challenges are search-ability and scalability. Data capability needs to be able to scale-out, up to hundreds of petabytes. Through embedded metadata, fine-grain search ability of enormous amount of data is desired.
Higher Education
Media and Entertainment
Higher Education
School research requires enormous amounts of data. While keeping workflows as simple as possible, data needs to be accessed by multiple users at the same time, and is used across a diverse range of computations.