Vectorized Intrinsics Can Be Replaced with Pure Java Code without Impairing Steady-State Performance

Several methods of the Java Class Library (JCL) rely on vectorized intrinsics. While these intrinsics undoubtedly lead to better performance, implementing them is extremely challenging, tedious, error-prone, and significantly increases the effort in understanding and maintaining the code. Moreover, their implementation is platform-dependent. An unexplored, easier-to-implement alternative is to replace vectorized intrinsics with portable Java code using the Java Vector API. However, this is attractive only if the Java code achieves similar steady-state performance as the intrinsics. This paper shows that this is the case. We focus on the hashCode and equals computations for byte arrays. We replace the platform-dependent vectorized intrinsics with pure-Java code employing the Java Vector API, resulting in similar steady-state performance. We show that our Java implementations are easy to fine-tune by exploiting characteristics of the input (i.e., the array length), while such tuning would be much more difficult and cumbersome in a vectorized intrinsic. Additionally, we propose a new vectorized hashCode computation for long arrays, for which a corresponding intrinsic is currently missing. We evaluate the performance of the tuned implementations on four popular benchmark suites, showing that the performance are in line with those of the original OpenJDK 21 with intrinsics. Finally, we describe a general approach to integrate code using the Java Vector API into the core classes of the JCL, which is challenging because premature use of the Java Vector API would crash the JVM during its fragile initialization phase. Our approach can be adopted by developers to modify JCL classes without any changes to the native codebase.