TornadoVM is an open-source framework that enables Java applications to execute on heterogeneous hardware accelerators, such as GPUs and FPGAs. While TornadoVM simplifies programmability, understanding and optimizing the performance of applications on heterogeneous systems remains a significant challenge.

Scaling up the performance of managed applications on Non-Uniform Memory Access (NUMA) architectures has been a challenging task, as it requires a good understanding of the underlying architecture and managed runtime environments (MRE). Prior work has studied this problem from the scope of specific components of the managed runtimes, such as the Garbage Collectors, as a means to increase the NUMA awareness in MREs.

Java benchmarking suites like Dacapo and Renaissance are employed by the research community to evaluate the performance of novel features in managed runtime systems. These suites encompass various applications with diverse behaviors in order to stress test different subsystems of a managed runtime. Therefore, understanding and characterizing the behavior of these benchmarks is important when trying to interpret experimental results.

The ever-growing demand for more memory capacity from applications has always been a challenging factor in computer architecture. The advent of the Non Unified Memory Access (NUMA) architecture has achieved to work around the physical constraints of a single processor by providing more system memory using pools of processors, each with their own memory elements, but with variable access times. However, the efficient exploitation of such computing systems is a non-trivial task for software engineers. We have observed that the performance of more than half of the applications picked from two distinct benchmark suites is negatively affected when running on a NUMA machine, in the absence of manual tuning. This finding motivated us to develop a new profiling tool, so called PerfUtil, to study, characterize and better understand why those benchmarks have sub-optimal performance on NUMA machines. PerfUtil's effectiveness is based on its ability to track numerous events throughout the system at the managed runtime system level, that, ultimately, assists in demystifying NUMA peculiarities and accurately characterize managed applications profiles.