Enhancing X10 performance by auto-tuning the managed java back-end

X10 is a programming language specifically de- signed with productivity and scalability in mind. In the era of distributed multi-core systems, X10 provides programmers a high-level abstraction which is an absolute necessity. In this paper we present an auto-tuning solution to enhance the performance of X10 programs that uses the Java back-end. Our auto-tuner is based on OpenTuner, an extensible framework for building auto-tuning applications. We present improved running times for X10 benchmark programs that are shipped with X10 and the well known LULESH benchmark. The auto-tuning experiments recorded a maximum performance improvement of 50% for LULESH while the average improvement for the set of benchmarks is 25%. We analyze the internal changes a Java Virtual Machine (JVM) undergoes as a result of our auto-tuning. Finally, the study of the behavior of tuned programs for their input sensitivity shows that our tuned JVM configurations would continue with enhanced performance over varying input sizes of a program.