High Performance Computing
Cloud HPC provides a flexible and cost-effective solution for organisations looking to harness the power of high-performance computing without the need for large capital investments in physical infrastructure.
Cloud HPC (High-Performance Computing) refers to the use of cloud computing resources to perform tasks that require significant computational power. HPC typically involves the use of specialised hardware and software configurations to solve complex problems that would be impractical to solve with standard computing resources.
Here are some key aspects of Cloud HPC:
Cloud HPC allows for the easy scaling of computational resources. You can dynamically allocate or de-allocate resources based on your needs. This is particularly useful for workloads that require a large number of processors for a short period of time.
Cloud HPC provides remote access to powerful computing resources, which can be particularly useful for researchers, scientists, and organisations that may not have access to their own HPC infrastructure.
While HPC can be expensive to set up and maintain on-premises, cloud-based solutions offer a pay-as-you-use model. This means you only pay for the resources you use, which can be more cost-effective for sporadic or variable workloads.
Different cloud providers offer a variety of HPC solutions, including virtual machines with high-performance capabilities, specialised HPC clusters, and even access to GPU-accelerated computing.
HPC often involves the parallel processing of data across multiple computing nodes. Cloud platforms can provide the infrastructure needed to support parallel computing tasks.
Cloud HPC often utilises distributed computing, where tasks are divided among multiple machines or nodes for faster processing. This allows for the handling of very large datasets or complex simulations.
Cloud providers offer various storage solutions, including high-performance storage systems that are optimised for HPC workloads.
Security and Compliance
Cloud providers typically offer robust security measures and compliance certifications to ensure that sensitive data and computations are handled securely.
Many cloud platforms provide tools for orchestrating the allocation and de-allocation of resources, allowing for efficient use of computing power.
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PeaSoup is a Cloud HPC provider. Liquid immersion cooling technology allows PeaSoup to deploy high-density servers, which are essential for delivering high-performance computing. PeaSoup also offers a variety of HPC-specific services, such as GPU-accelerated computing and high-speed networking.
Here are some features and capabilities that make PeaSoup a good fit for HPC workloads:
Customers have more computing power and can deploy faster and more reliable applications. Immersion cooling can help to reduce the risk of hardware failure. This is important for applications that need to be available 24/7, such as business-critical applications and e-commerce websites.
PeaSoup offers a variety of GPU-accelerated compute instances. This is important for HPC workloads that require the high performance of GPUs, such as scientific simulations and AI/ML training.
PeaSoup offers high-speed networking fabrics for connecting compute nodes. This is essential for HPC workloads that need to communicate with each other quickly.
PeaSoup offers a variety of pricing options, including spot pricing and reserved instances. This allows customers to choose the pricing option that best meets their needs and budget. Our HPC service is offered in two options – a Private Cloud and a Bare Metal as a Service.
PeaSoup is a great choice for HPC workloads because it offers a combination of high-performance computing capabilities, flexible pricing, and a wide range of services.
Here are some examples of HPC workloads that PeaSoup is well-suited for:
- Scientific simulations, such as weather forecasting, climate modelling, and drug discovery
- Engineering simulations, such as CFD and FEA
- AI/ML training and deployment
- Data Analytics
- Video Rendering
- Financial modelling