Hardware, software and best practices for data center HPC
High-performance computing enables organizations to use parallel processing to run advanced programs such as AI and data analytics. The technology combines the processing power of multiple computers to handle complex computing tasks.
When implemented correctly, high-performance computing (HPC) can help organizations handle big data. The technology requires specialized hardware, software frameworks and often large facilities to house it all. HPC also comes with a high price tag, which can act as a barrier to many organizations hoping to implement HPC in their data centers.
To determine whether your organization could benefit from HPC, consider the complexity of computing tasks your data center handles, the budget you can feasibly allocate toward obtaining and running numerous servers, the expertise and training requirements of your staff and the size of your data center facilities. Data centers that handle compute-intensive tasks, such as government resource tracking or financial risk modeling, and data centers that lean heavily on AI and machine learning can benefit greatly from HPC. But if your organization might struggle to keep an HPC cluster busy, it might not be worth the investment.
Once you decide to implement HPC, take stock of the various investments you must make. Understand which networking and processing hardware you require; what tools you intend to use to monitor, provision and manage your HPC cluster; which big data framework suits your data processing needs; and what you intend to use HPC for. Once you've considered all these areas, you can put plans in place to troubleshoot any complications and ensure the HPC cluster runs smoothly.
