Performance evaluation of Java/PCJ implementation of parallel algorithms on the cloud (extended version)

<jats:title>Abstract</jats:title><jats:p>Large‐scale computing and data processing with cloud resources is gaining popularity. However, the usage of the cloud differs from traditional high‐performance computing (HPC) systems and both algorithms and codes have to be adjusted. This work is often time‐consuming and performance is not guaranteed. To address this problem we have developed the PCJ library (parallel computing in Java), a novel tool for scalable HPC and big data processing in Java. In this article, we present a performance evaluation of parallel applications implemented in Java using the PCJ library. The performance evaluation is based on the examples of highly scalable applications of different characteristics focusing on CPU, communication or I/O. They run on the traditional HPC system and Amazon web services Cloud as well as Linaro Developer Cloud. For the clouds, we have used Intel x86 and ARM processors for running Java codes without changing any line of the program code and without the need for time‐consuming recompilation. Presented applications have been parallelized using the partitioned global address space programming model and its realization in the PCJ library. Our results prove that the PCJ library, due to its performance and ability to create simple portable code, has great promise to be successful for the parallelization of various applications and run them on the cloud with a performance close to HPC systems.</jats:p>