THANK YOU FOR SUBSCRIBING
Organizations only pay for the capacity they use with HPC in the cloud, and there's no risk of on-premises infrastructure becoming obsolete or underutilized. Also, cloud-based services allow unrestricted innovation by providing quick results and greater flexibility.
Fremont CA: Cloud computing facilitates High Performance Computing (HPC) by putting powerful computational potentials in the hands of more researchers, engineers, and organizations who may not have access to adequate on-premises infrastructure. The flexibility and scalability of the cloud provide virtually unlimited capacity, reducing wait times and job queues. In addition, it's simple to expand and update workflows, such as merging Artificial Intelligence (AI) with HPC, thanks to access to new and evolving services and applications.
Here are four challenges facing HPC in the cloud:
Cost and Cost Management
The cost of running HPC in the cloud is a significant concern for many organizations. When looking at the expense of cloud-based HPC systems, companies should keep in mind that a simple TCO analysis does not always tell the whole story. Demand for on-premises HPC resources frequently exceeds capacity, and lost productivity due to an overburdened system has far-reaching consequences for businesses that place a premium on the speed of innovation. Moving HPC workloads to the cloud also eliminates the need for three to five-year technology and infrastructure refresh cycles, ensuring that innovation keeps moving forward.
Data Security and Data Governance
Cloud security concerns are common. Many industries that rely heavily on HPC have stringent security requirements, and cloud-based HPC solutions face this challenge. While some see on-premises HPC as having security and privacy advantages, they overlook risk management issues such as aging infrastructure, which raises the security costs of maintaining compliance and the high costs of regulatory compliance and certifications that are frequently required for on-premises solutions.
Transferring data and HPC to the cloud increases productivity by freeing precious financial and human resources while also lowering company risks by keeping data in a more resilient and secure environment. Furthermore, cloud-based HPC enables clients to mine all of the data accessible from HPC simulations using AI, machine learning, and deep learning, reducing the number of simulations necessary and resulting in cheaper and faster HPC workload execution. Improved performance in the cloud can give higher ROI because newer, cloud-native HPC programs were built to perform better on cloud-based elastic infrastructure.
Excellent-performance computing (HPC) users want high performance, yet many still believe the cloud can't compete with on-premises data centers. However, the notion that the networking speed between cloud compute nodes is insufficient for good performance is outmoded. Recent advances have improved cloud networking and reduced latency to the point that all but the most resource-intensive HPC applications perform better in the cloud as on-premises infrastructure.