Improving Native-Image Startup Performance

Abstract

With the increasing popularity of Serverless computing and Function as a Service---where typical workloads have a short lifetime---the research community is increasingly focusing on startup performance optimization. To reduce the startup time of managed language runtime systems, related work proposes strategies to move runtime environment initialization ahead-of-time. For instance, GraalVM Native Image allows one to create a binary file from a Java application that embeds a snapshot of the pre-initialized heap memory and can run without instantiating a Java Virtual Machine. However, the program startup needs to be further optimized, because the cloud runtime often starts the program while responding to the request. Thus, the program startup time impacts the service-level agreement. In this paper, we improve the startup time of Native-Image binaries by changing their layout during compilation, reducing I/O traffic. We propose a profile-guided binary-reordering approach and a profiling methodology to obtain the execution-order profiles of methods and objects. Thanks to these profiles, we first reduce page faults related to the code section. Then, we propose three ordering strategies to reduce page faults related to accessing the objects in the heap snapshot. Since the object identities and the heap-snapshot contents are not persistent across Native-Image builds of the same program, we propose a method of matching objects from the profile against the objects in the profile-guided build. Experimental results show that our ordering strategies lead to an average page-fault reduction factor of 1.61× and an average execution-time speedup of 1.59×.