In compute intensive workloads, the goal is to distribute the work for a single problem across multiple CPUs to reduce the execution time as much as possible. In order for us to do this, we need to execute steps of the problem in parallel. Each process¬—or thread—takes a portion of the work and performs the computations concurrently. The CPUs typically need to exchange information rapidly, requiring specialization communication hardware. Examples of these types of problems are those that can be found when analyzing data that is relative to tasks like financial modeling and risk exposure in both traditional business and healthcare use cases. This is probably the largest portion of HPC problem sets and is the traditional domain of HPC.
Previously codenamed, AMD EPYC™ will deliver the highly successful “Zen” x86 processing engine scaling up to 32 physical cores. Key features;