Benefits of doing HPC on the cloud

With virtually unlimited capacity on the cloud, you can move beyond the constraints of on-premises HPC. You can reimagine new approaches based on the business use case, experiment faster, and gain insights from large amounts of data, without the need for costly on-premises upgrades and long procurement cycles. You can run complex simulations and deep learning models in the cloud and quickly move from idea to market using scalable compute capacity, high-performance storage, and high-throughput networking. In summary, it enables you to drive innovation, collaborate among distributed teams, improve operational efficiency, and optimize performance and cost. Let’s take a deeper look into each of these benefits.

Drives innovation

Moving HPC workloads to the cloud, helps you break barriers to innovation, and opens the door for unlimited possibilities. You can quickly fail forward, try out thousands of experiments, and make business decisions based on data. The benefit that I really like is that, once you solve the problem, it remains solved and you don’t have to revisit it after a system upgrade or a technology refresh. It eliminates reworking and the maintenance of hardware, lets you focus on the business use case, and enables you to quickly design, develop, and test new products. The elasticity offered by the cloud, allows you to grow and shrink the infrastructure as per the requirements. Additionally, cloud-based services offer native features, which remove the heavy lifting and let you adopt tested and verified HPC applications, without having to write and manage all the utility libraries on your own.

Enables secure collaboration among distributed teams

HPC workloads on the cloud allow you to share designs, data, visualizations, and other artifacts globally with your teams, without the need to duplicate or proliferate sensitive data. For example, building a digital twin (a real-time digital counterpart of a physical object) can help in predictive maintenance. It can get the state of the object in real time and it monitors and diagnoses the object (asset) to optimize its performance and utilization. To build a digital twin, a cross-team skill set is needed, which might be remotely located to capture data from various IoT sensors, performing extensive what-if analysis and meticulously building a simulation model to develop an accurate representation of the physical object. The cloud provides a collaboration platform, where different teams can interact with a simulation model in near real time, without moving or copying data to different locations, and ensures compliance with rapidly changing industry regulations. Moreover, you can use native features and services offered by the cloud, for example, AWS IoT TwinMaker, which can use the existing data from multiple sources, create virtual replicas of physical systems, and combine 3D models to give you a holistic view of your operations faster and with less effort. With a broad global presence of HPC technologies on the cloud, it allows you to work together with your remote teams across different geographies without trading off security and cost.

Amplifies operational efficiency

Operational efficiency means that you are able to support the development and execution of workloads, gain insights, and continuously improve the processes that are supporting your applications. The design principles and best practices include automating processes, making frequent and reversible changes, refining your operations frequently, and being able to anticipate and recover from failures. Having your HPC applications on the cloud enables you to do that, as you can version control your infrastructure as code, similar to your application code, and integrate it with your Continuous Integration and Continuous Delivery (CI/CD) pipelines. Additionally, with on-demand access to unlimited compute capacity, you will no longer have to wait in long queues for your jobs to run. You can skip the wait and focus on solving business critical problems, providing you with the right tools for the right job.

Optimizes performance

Performance optimization involves the ability to use resources efficiently and to be able to maintain them as the application changes or evolves. Some of the best practices include making the implementation easier for your team, using serverless architectures where possible, and being able to experiment faster. For example, developing ML models and integrating them into your application requires special expertise, which can be alleviated by using out-of-the-box models provided by cloud vendors, such as services in the AI and ML stack by AWS. Moreover, you can leverage the compute, storage, and networking services specially designed for HPC and eliminate long procurement cycles for specialized hardware. You can quickly carry out benchmarking or load testing and use that data to optimize your workloads without worrying about cost, as you only pay for the amount of time you are using the resources on the cloud. We will understand this concept more in Chapters 5, Data Analysis, and Chapter 6, Distributed Training of Machine Learning Models.

Optimizes cost

Cost optimization is a continuous process of monitoring and improving resource utilization over an application’s life cycle. By adopting the pay-as-you-go consumption model and increasing or decreasing the usage depending on the business needs, you can achieve potential cost savings. You can quickly commission and decommission HPC clusters in minutes, instead of days or weeks. This lets you gain access to resources rapidly, as and when needed. You can measure the overall efficiency by calculating the business value achieved and the cost of delivery. With this data, you can make informed decisions as well as understanding the gains from increasing the application’s functionality and reducing cost.

Running HPC in the cloud helps you overcome the limitations associated with traditional on-premises infrastructure: fixed capacity, long procurement cycles, technology obsolescence, high upfront capital investment, maintaining the hardware, and applying regular Operating System (OS) and software updates. The cloud gives you unlimited HPC capacity virtually, with the latest technology to promote innovation, which helps you design your architecture based on business needs instead of available hardware, minimizes the need for job queues, and improves operational and performance efficiency while still optimizing cost.

Next, let’s see how different industries such as Autonomous Vehicles (AVs), manufacturing, media and entertainment, life sciences, and financial services are driving innovation with HPC workloads.