Benefits of Cloud GPU for High-Performance Computing
Our High-Performance Computing (HPC) solutions offer numerous benefits across various industries and applications.
SLURM integration in our Deep Learning solutions offers streamlined job scheduling and workload management, ensuring optimal utilisation of resources for faster, more efficient deep learning model training.
With Kubernetes compatibility, our Deep Learning platform enhances orchestration and automation of containerised applications, providing scalable and resilient infrastructure to handle complex deep learning tasks seamlessly.
Advanced Scientific Research:
HPC speeds up intricate simulations and analysis of vast datasets, benefiting astrophysics, climate modelling, molecular dynamics, and particle physics, enhancing understanding of complex phenomena.
HPC speeds drug discovery through molecular simulations, hastening new drug development. In healthcare, it aids medical imaging, genomics, and personalised medicine.
HPC is pivotal in financial services, facilitating intricate risk analysis, portfolio optimisation, algorithmic trading, and market scenario simulations. GPUs speed up computations, leading to quicker decisions in the finance sector.
HPC is crucial for high-computation numerical weather models. Precise forecasts support disaster readiness, agriculture, and weather-sensitive industries.
HPC is vital for processing massive datasets from studies, simulations, or experiments. It reveals patterns and correlations that traditional computing struggles to uncover.
Hyperstack offers the tools to develop a range of HPC solutions on cutting-edge NVIDIA GPUs.
NVIDIA Earth-2: Is a full-stack open platform that speeds up climate and weather predictions using detailed simulations. It encompasses physical models (ICON, IFS), neural networks (FourCastNet, GraphCast, DLWP via NVIDIA Modulus), and data management/visualisation (NVIDIA Omniverse). Powered by NVIDIA DGX H100, Earth-2 enables fast and large-scale global atmosphere simulation and visualisation.
Physics-Informed Machine Learning
NVIDIA Modulus: is an open-source physics AI framework. Create, train, and refine models via Python. Blend physics and simulation for quick, accurate predictions. Using Modulus, engineers create accurate AI surrogate models merging physics and simulation for instant predictions in customised designs. Boost engineering simulations with AI for digital twins across physics domains like CFD, structural analysis, and electromagnetics.
NVIDIA's cuQuantum is an SDK with optimised tools to accelerate quantum workflows. Using NVIDIA Tensor Core GPUs, cuQuantum drastically speeds up quantum circuit simulations, making them significantly faster. The cuQuantum Appliance helps developers by providing simulation software in an optimised container for use on the latest NVIDIA DGX and HGX systems.
High-Performance Computing is used in healthcare, trading, business, and many other fields, transforming industries and improving efficiency.
Healthcare (protein pose prediction, molecular simulation)
Real-time video streaming analysis
Classify images for self-driving cars, medical imaging diagnosis, and others
Analyse financial data to predict market trends, assess risk, and optimise investment strategies
GPUs we Recommend for High-Performance Computing
Elevate your HPC solutions with the Hyperstacks cloud GPU family from NVIDIA.
Significantly outperforms traditional CPUs in high-performance computing (HPC) workloads, offering an inference speed that is 237 times faster
Up to 10X higher performance for applications that process terabytes of data.
RTX A6000 / RTX A40
Demonstrates impressive performance for stable diffusion tasks in high-performance computing (HPC) workloads.
Frequently Asked Questions
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Why is GPU essential in building a high-performance computer?
A GPU is essential in building a high-performance computer because it's exceptional at handling multiple tasks at once, unlike CPUs. Specifically built for parallel processing, GPUs shine in data-heavy tasks like AI, simulations, and scientific modelling. Their specialised design and swift memory access enable fast calculations, significantly speeding up tasks that require immense computations. GPUs serve as powerhouse accelerators, boosting overall performance and efficiency in tackling demanding workloads within computers, especially in scenarios where rapid processing is key.
What is the best operating system for HPC?
CentOS is considered one of the best operating systems for HPC. Many top HPC clusters choose it because it's stable, reliable, and runs like a champ.
Want to learn more about which OS you can choose for your virtual machine? Check out Hyperstack’s documentation now!
What are the key considerations when selecting a GPU for high-performance computing applications?
Here are the key considerations when selecting a GPU for high-performance computing applications:
- Processing Power (TFLOPs): Look for GPUs with high floating-point performance (measured in TFLOPs) as it directly impacts computational capability.
- Memory Bandwidth: Consider the GPU's memory capacity and bandwidth to ensure it can efficiently handle the data requirements of your specific application.
- Precision: Some GPUs excel in specific types of calculations or precision (e.g., single-precision, double-precision), so choose one that aligns with your computing needs.
- Software Compatibility: Check for compatibility with the software tools and frameworks you plan to use for your HPC tasks.
- Budget: Assess the cost-performance ratio of different GPUs and choose one that fits within your budget. Hyperstack offers transparent pricing and flexible billing options, allowing you to scale your resources precisely to your needs.
Visit Hyperstack to find the perfect GPU configuration for your specific needs.
See What Our Customers Think...
“This is the fastest GPU service I have ever used.”
You guys rock!! You have NO IDEA how badly I need a solid GPU cloud provider. AWS/Azure are literally only for enterprise clients at this point, it's impossible to build a highly technical startup and get hit with their ridiculous egrees fees. You guys have excellent latency all the way down here to Atlanta from CA.
By far the most important aspect of a cloud provider, only second to cost/quality ratio, is their API. The UI/UX of the console is extremely well designed and I appreciate the quality. So, I’ll be diving into your API deeply. Other GPU providers don’t offer a programmatic way of creating OS images, so the fact that you do is key for me.