Impact of Containerization on Low-Cost Post Moore Computing Architectures

Virtualization is a well-known option to deploy execution environments on diverse platforms, but the number of additional layers makes it unattractive due to the complexity and performance cost. In recent years, containerization has taken shape and strength as a method of application deployment in High-Performance Computing (HPC) environments because it is visible the low impact on performance and the easy integration with the system, reducing complexity. Therefore, this work develops a series of tests whose workloads show the effects on the computation when applications are containerized. Workloads include complex floating-point operations, calculation of prime numbers, or matrix operations. The results present the impact of containerization on computational efficiency, performance, runtime, and power consumption on low-cost Post-Moore computing architectures.