AI and HPC in the Cloud
3XS AIC-A40-4G-64E = 64 x vCPU Cores, 384GB RAM, 4 x 48GB vGPU Memory, 2TB Storage, Ubuntu OS - Monthly Subscription
3XS AI and HPC in the Cloud
GPU-accelerated virtual machines for data scientists3XS Systems dev boxes and servers are the gold standard when it comes to developing and training Deep Learning and Machine Learning models, big data analytics and running high performance computing simulations. Powered by professional-grade NVIDIA RTX GPU accelerators, all the capabilities of our award-winning 3XS systems are now available in the cloud from any device, anywhere. 3XS AI and HPC, powered by Scan Cloud, enables any organisation to take advantage of highly responsive GPU-accelerated compute without the need to invest in on-premise hardware and its associated maintenance. Available in rental increments as small as one month, 3XS AI and HPC profiles can be used as little or as often as needed.
GPU-acceleratedNVIDIA RTX GPUs lie at the heart of our cloud service, delivering cutting edge performance and features for data science workloads.
ScalableAs your business needs develop additional virtual machines can be quickly spun up and additional storage brought online.
FlexibleVirtual machines are available in a wide range of configurations, tuned for the different users and workloads in your organisation.
Cost-effectiveAvailable in monthly commitments paid for from OPEX, there is no upfront outlay from CAPEX or ongoing maintenance costs associated with on-premise hardware.
SecureVirtual machines are hosted in secure datacentre environments so the cloud experience will not compromise the integrity of your data.
TrustedAs an NVIDIA partner, Scan provides guidance throughout your cloud service - from a free guided proof of concept to personalised virtual machine configurations.
Optimised for Deep Learning & AI and HPC
We understand how important it is to tune virtual machines for specific workloads and applications. 3XS AI and HPC includes multiple profiles, specifically designed for data science workloads. As the profiles support any standard Linux-based applications, our specialists can create a custom profile for you if required.
Data PreparationData preparation is the process of readying data for the development, training, testing and implementation of an algorithm. It’s a multi-step process that involves data collection, structuring and cleaning, feature engineering, and labelling. These steps play an important role in the overall quality of your deep learning model, as they build on each other to ensure a model performs to expectations. We can provide profiles specifically tailored for data preparation with expanded storage.
DevelopmentOnce the data is ready it can be used withs the libraries and frameworks to begin building your AI models. Model development usually begins with smaller and lower complexity models with smaller data sets. However this can be a very iterative process very early on in the development model cycle. This development stage can be carried out on relatively low powered hardware – typically one or two GPUs is sufficient, although more GPUs will reduce the time to your ideal version.
TrainingThe training of deep learning and machine learning models happens with large datasets and is very iterative. As model developers train, calibrate and re-calibrate parameters and hyperparameters of the models, large data volumes are needed to be repeatedly passed through the models. This process can be very resource hungry in terms of compute, storage, memory, bandwidth. That’s why our training profiles have multiple GPUs with optimised hardware to help speed up training tasks.
HPCNVIDIA GPUs have revolutionised high performance computing and big data, enabling far quicker time to results and analysis than when run on traditional CPUs. Our HPC virtual machines, powered by multiple NVIDIA GPUs, CUDA-X and NVIDIA HPC SDK, are available in a wide variety of specifications, each optimised for different levels of precision, allowing you to select the perfect configuration for your project.
Accelerated by NVIDIA RTX GPUs
The most powerful professional data science and compute GPUs are the NVIDIA RTX series. RTX GPUs, delivered virtually by 3XS AI and HPC in the cloud, bring a host of features to data scientists, enabling far greater control and capability.
NVIDIA CUDANVIDIA CUDA is a parallel computing platform and programming model for compute applications. With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of NVIDIA GPUs. In GPU-accelerated applications, the sequential parts of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C++, Python and MATLAB.
NVIDIA GPU CloudThe NVIDIA GPU Cloud (NGC) provides researchers and data scientists with simple access to a comprehensive catalogue of GPU-optimised software tools for deep learning and high performance computing (HPC) that take full advantage of NVIDIA GPUs. The NGC container registry features NVIDIA tuned, tested, certified, and curated containers for the top deep learning frameworks and applications. It also offers third-party managed HPC application containers, NVIDIA HPC visualisation containers, and partner applications.
Features of Scan Cloud
Each 3XS AI and HPC virtual machine is provided with at least 1TB of high performance SSD storage for the operating system and applications. Storage of project data is provided via AI and HPC-optimised storage nodes that can be accessed by the virtual machines in your account. Our application specialists will work with you to identify the optimum capacity for this shared storage, which can be easily scaled as your needs develop.
New 3XS AI and HPC virtual machines can be spun up rapidly, with a fresh install of Ubuntu or your preferred operating system ready to go. All you need to do is install and license your applications and you can start work right away.
Our AI and HPC virtual machines contain multiple GPUs and deliver enormous performance and workload throughput capabilities, but usually only for a single user per virtual machines. GPU pooling consolidates these resources in order to gain greater control and visibility.
Run:AI software decouples data science workloads from the GPU resources. By pooling resources and applying an advanced scheduling mechanism to data science workflows, Run:AI greatly increases the ability to fully utilise all available resources, from pooled GPUs to fractional GPUs. Run:AI capability can be easily added to your AI and HPC virtual machines, with a minimum of eight physical GPUs required for deployment.
Find out more
The 3XS AI and HPC in the cloud offering, delivered in conjunction with our secure datacentre partner, has been designed from the ground and includes optimised appliances at every stage of the architecture to reduce bottlenecks and ensure scalability. Unlike other remote GPU-accelerated services these environments are supported by a full team of expert AI and HPC consultants including application specialists, software engineers and hardware architects to supported your cloud experience.
Start using 3XS Cloud Workstations todaySpeak to our Cloud Workstation team to arrange a demo or start renting workstation instances.
Deploy your own 3XS Cloud WorkstationsPrefer to go the private cloud route? We can also provide a full deployment of hardware and software, fully configured to deploy your own private cloud workstations.