Private GPU Cloud for Education

Create a cloud-driven learning environment to evolve with the demands of academic users
Private GPU Cloud creates a modern and digital learning and teaching experience for any educational institution.

check_circle_outlineCost Efficiency

check_circle_outlineEasy IT Management

check_circle_outlineScalability

check_circle_outlineEnterprise-level Security

Deployment & Services

What is Private GPU Cloud for Education?

Educational institutions, now more than ever, require an agile infrastructure to meet the challenges of modern education. With tighter budgets, IT must ensure security and provide technolologies to support distance learning and remote working. Traditional Virtual Desktop Infrastructure (VDI) and public clouds, however, are often costly, resource-intensive and difficult to set up, operate and maintain without having an IT expert team in-house. 

Taking your worries away from the physical setup and the enablement of cloud-based services, Private GPU Cloud is a cloud delivery model that helps campuses modernise their infrastructure on-premises. With less complexity and additional overhead costs, Cloudalize offers all the required hardware to set up an optimised cloud environment with competitive pricing and a managed GPU-enabled platform – an application and desktop delivery solution for you to create the most effective digital learning experience anywhere and on any device. 

Your institution can leverage Private GPU Cloud to accelerate learning innovation on- or off-campus, such as cloud classrooms, online computer labs, virtual research labs, and Bring-your-own-device (BYOD) policies. 

Unlike CPU-powered VDI, Cloudalize’s platform is unique and proprietary technology designed for graphical-processing units (GPU) – 1,000 times faster than CPU. Clients will benefit from a cloud technology that keeps evolving with your educational needs.  

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Cloudalize's Private Cloud gives you the power of GPU power on-premises to obtain greater speed and performance in your daily educational and working life.

How Private GPU Cloud

Enables a New Way of Learning

Cloud Classrooms

Cloud Classrooms are the Cloudalize way of teaching. It shifts the focus from physical to the Cloud. Cloud Workstations, a GPU-enabled Desktop-as-a-Service, allow users to easily access course content, applications, and data over 4G, 5G or Wi-Fi. Place and time are no longer barriers to learning. Teachers can collaborate with others on the same project or instantly upload learning materials anywhere. Students can easily learn or do group work at home or while on the go on a shared file and with access to the most updated course content.

Similarly, you can set up a virtual classroom and enable BYOD policies to bridge the gap where traditional classroom setup is not allowed. Virtual learning reduces both the infrastructural costs for physical classrooms and expenses of onboarding regular teachers in a faculty. They can create and deliver lessons on their devices from remotely – matching the convenience of accessing learning at the fingertips.

Learn More about Cloud Workstations
Cloudalize's Cloud Classrooms are available on Private GPU Cloud to enable distance learning with specialised software from Autodesk, Adobe, Lumion.
The Cloudalize Campus has GPU power on-premises with Cloudalize to power all requirements of education: students, faculty and remote professors.

On-campus or Online Computer Labs

Cloudalize expands the use of the traditional computer labs used for lectures, presentations or focused group work. Cloudalize’s technology can be installed on the computers on-campus but access can be granted to any device off-campus. This extends the life of older legacy machines but gives the flexibly to institutions to implement a BYOD policy.

Having uninterrupted access to computer labs is important for students who need high-spec computers to do coursework and learn specialised programs such as Autodesk software or Adobe Suite. Built on cutting-edge GPU technology, Cloudalize Cloud Workstations offer high performance online computer lab environments – customised to suit your curriculum or training package.

Virtual Research Labs

The potential of the cloud is unmatched when it comes to resource allocation. Research scholars, particularly in the field of design and engineering, require more compute resources for demanding tasks such as creative production (graphics and video rendering), high-performance computing (HPC), and Artificial Intelligence (AI). You can quickly set up a virtual research lab within the private cloud environment and optimise resource allocation with Kubernetes GPU Cloud.

Kubernetes GPU Cloud is a Cloudalize technology that helps you effectively utilise the hardware 24/7 for research during the evening or off-peak hours. You can thus achieve economies-of-scale for your private cloud, as idle resources can be shared for animation rendering or AI calculations, which will provide a solid backing for animation teaching, research and experiment.

Learn More about Kubnetes GPU Cloud
Cloudalize's GPU Cloud enables Kubernetes for machine learning, advanced research on- and off-campus via Kubernetes GPU Cloud.
Private GPU Cloud enables you to have a Bring-Your-Own-Device educational policy. Teach and learn from smartphone, tablet, MacBook or Desktop Computer with Private GPU Cloud.

Bring-Your-Own-Device (BYOD)

BYOD refers to educators and students using their own mobile devices, such as smartphones, laptops and tablets to connect to their organizational networks and access work-related or course-related systems and potentially sensitive or confidential data.

With a cloud-based platform as Cloudalize, the requirements of hardware resources are minimal, and security is guaranteed. Applications can operate seamlessly on internet browsers or via a gateway on different devices. Students can still access everything in a cloud-based storage and learn with any low-end devices that they own – eliminating investment in an expensive computer for taking specialised courses. Learning made simpler with the cloud!

Why Private GPU Cloud

for Education?

Private GPU Cloud allows your educational institution to obtain GPU technology on-campus meaning more processing power and speed without spending a lot.
Cost Efficiency

Different from VDI, you will obtain guaranteed performance without budgeting for all the add-ons and recommended engineering services to optimise your cloud environment. Your institution will save more not only on overhead costs but also on your hardware investment due to our competitive pricing and cloud optimisation knowledge – all in a total package.

Private GPU Cloud enables flexibility to manage educational resources based on supply and demand during the day or during the night to optimise usage and cost.
Easy IT Management

Cloudalize wants to make cloud simple, clear and easy-to-use for both end users and administrators. Private GPU Cloud comes with a straightforward admin portal. You can easily manage users and their access rights on the platform as well as create blueprints for different classes and deploy them as needed.
 

Cloudalize Private GPU Cloud allows your business or institution to manage capacity (scale-up and down) with demand when required by your IT.
Scalability

A scalable private cloud refers to the ability of the cloud to enable multiple applications rapidly and easily. Capable of delivering high-powered cloud workstations, application streaming and Kubernetes for compute needs, you can use the Cloudalize’s platform according to your application demand. For example, assigning resources for an online computer lab during course hours and reallocating compute power for a virtual research centre on the same hardware at off-peak times. 

Private GPU Cloud brings market-leading security features to your campus with GPU power.
Enterprise-level Security

You can control access to the network and roll out cloud services in a secure environment, as our platform enables both single- and multi-tenancy – separating departments in your school, college, or university, each with its own organizational unit including a private network and isolating each project in its own private network container.  

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