How cloud technology can benefit your organisation
Read our case studies and learn how Cloud technology help your organisation
Cloud computing is on the rise in every industry, whether to mitigate upfront investment, drive flexible working practices or as a burst resource to cope with unpredictable workloads. With this in mind, the Scan Cloud portfolio of virtual GPU (vGPU) services has been created so you have an alternative to deploying physical IT hardware as your organisation expands or develops.
Case Studies
Cloud Computing in the Pro Graphics sector
Advanced visualisation within industries such as manufacturing and construction have driven the need for ever more powerful ways of appreciating products, vehicles or buildings prior to their physical development. Professional graphics applications cover a huge range of capabilities and are now used for projects large and small - both with increasing complexity. Not only does cloud computing lend flexibility to scenarios where GPU demands may change week-to-week, it also adds an element of productivity in the ability to take laptops or tablets onsite and still access incredibly detailed plans or blueprints - something just not possible with bulky desktop workstations.
AEC & BIM
Architecture, Engineering and Construction software applications and Building Information Modelling applications use very different GPU resource so the flexibility to dynamically switch between cloud profiles as needs arise and change could prove a very effective business tool.
CAD & CAE
Computer Aided Engineering applications take this process a step further with the ability to then analyse these models - in short, CAD is the process of designing a product and CAE is when you simulate and test it. Both tasks lend themselves well to vGPU as the resource required my differ project to project.
Media & Entertainment
The M&E industry is one that continues to grow exponentially with more advanced Computer Generated Imagery (CGI) being used in almost all TV and films. Employing Cloud GPU enables the sizing and scaling of the required resource at a moment’s notice.
Advanced Computer Generated Imagery (CGI) within industries such as film and television production have driven the need for ever more creative ways of enhancing professional video content. Applications cover a huge range of capabilities and are now used for projects large and small - both with increasing complexity. Not only does cloud computing lend flexibility to scenarios where GPU demands may change week-to-week, it also adds an element of productivity in the ability to take laptops or tablets to a location or studio and still access incredibly detailed effects and scenes - something just not possible with bulky desktop workstations.
Editing
Non Linear Editing requires a well-balanced system configuration with a blend of CPU cores plus GPU resource and enough RAM and high-performance storage for the resolution you are working at. Cloud GPUs offer flexibility for this to change project by project with no wasted resource.
Colour Grading
While Colour Grading requires a system with a respectable CPU, RAM and storage, the key to responsive performance is one or more NVIDIA RTX GPUs - this can be effectively scaled as needed by simply swapping GPU profiles.
Visual FX
VFX is a key component in every project, from film making to video games and television production. We understand the unique requirements of VFX applications and have NVIDIA RTX GPU-heavy profiles with large RAM capacities, ideally suited to this demanding task.
Large professional graphics and video projects require equally large rendering resource too. With advancing size and complexity of design, TV and film projects this rendering resource is often required to be separate from any editing, production or engineering applications that may be is use at earlier stages of a project. Rather than doubling up on hardware for the task, cloud rendering is becoming more popular as it allows business to simply rent the vast GPU resource to complete large rendering tasks as and when needed.
Rendering
Rendering makes use of a scene file consisting of multiple 3D images or 3D models, which contains all relevant information in a predefined format such as the geometry, texture, viewpoint, and lightning descriptions, to name a few. The more complex the scene the more GPU power is required to render it, so cloud is a very attractive and cost-effective way to not invest or tie-up expensive resource.
GPU Profiles
GPUs are ideal for rendering as they have thousands of cores working parallel. A render that will take a CPU hours may be complete in minutes on a GPU. However, there may be some tasks where some intricate detail may be lost. GPU profiles can be scaled easily, so performance can be delivered through as many cores as necessary for rapid results.
CPU Profiles
CPUs are sometimes better at rendering intricate projects, as they can smoothly handle a set of more diverse tasks that require different computing operations, as opposed to GPUs which are designed to process huge chunks of data by executing them in the same way over and over again. Bespoke CPU profiles can be specified is required by the Scan Cloud team.
As companies expand it is often easier to scale PC resource through a centrally administered Virtualised Desktop Infrastructure (VDI). This means only low powered thin clients or NUCs are used at the desk, instead of full PCs, as any memory and GPU resource are allocated from cloud server hardware. Desktop profiles are assigned by user or team and adding extra profiles is simple to keeps costs low and manageability high.
Scalable and Flexible
When deploying a VDI it is important to have a PC profile that will meet your specific needs. The 3XS Cloud PC provides a single profile, specifically designed for the most popular everyday workloads such as applications from the Microsoft Office suite. General office productivity applications enable efficiency in the workplace, and even the simple tools found in Microsoft Windows and Office, on web browsers, and in streaming video can all benefit from GPU acceleration. It is also important to be able to deliver consistent performance to these vital applications to a variety of devices.
The rise of GPUs, delivering hugely parallel compute power, and the growth in available data has led to the ability to analyse a much greater proportion of an organisation’s data - and more crucially - in much shorter timeframes than ever before. This provides the opportunity to employ Artificial Intelligence (AI) and High Performance Computing (HPC) techniques to gain insight and drive learnings and predictions from data. The huge range of GPUs on the market enable even a single workstation to add value by rapidly analysing datasets, and for larger projects the sky is the limit when it comes to GPU-accelerated datacentres. However, this type of hardware can be expensive and as workloads adapt and change, the need to have flexible GPU resource is likely - this is where vGPU services come into their own.
Development
Model development usually begins with smaller datasets and lower complexity. However this can be a very iterative process very early on in the development cycle, so the ability to easily scale GPU resource can prove very useful and cost-effective - you only pay for what you use.
Training
The training of deep learning and machine learning models happens with much larger datasets, but is also very iterative. The ability to scale to multiple cloud GPUs and virtualise the GPU pool offer the most scalable way to train AI models in the fastest and cost-effective way.
HPC
NVIDIA GPUs have revolutionised high performance computing and big data, enabling far quicker time to results and analysis than when run on traditional CPUs. All our cloud GPU profiles support NVIDIA RAPIDS and CUDA-X to enable flexible HPC compute power without the hardware costs
