As software becomes increasingly complex and difficult to analyze, it is more and more common for developers to use high-level, type-safe, object-oriented (OO) programming languages and to architect systems that comprise multiple components. Different components are often implemented in different programming languages. In state-of-the-art multi-component, multi-language systems, cross-component communication relies on remote procedure calls (RPC) and message passing. As components are increasingly co-located on the same physical machine to ensure high utilization of multi-core systems, there is a growing potential for using shared memory for cross-language cross-runtime communication.
We present the design and implementation of Co-Located Runtime Sharing (CoLoRS), a system that enables cross-language, cross-runtime type-safe, transparent shared memory. CoLoRS provides object sharing for co-located OO runtimes for both static and dynamic languages. CoLoRS defines a novel language-neutral object/class model, which is a static-dynamic hybrid and enables class evolution while maintaining the space/time efficiency of a static model. CoLoRS uses type mapping and class versioning to transparently map shared types to private types. CoLoRS also contributes a synchronization mechanism and a parallel, concurrent, on-the-fly GC algorithm, both designed to facilitate cross-language cross-runtime object sharing.
We implement CoLoRS in open-source, production-quality runtimes for Python and Java. Our empirical evaluation shows that CoLoRS extensions impose low overhead. We also investigate RPC over CoLoRS and find that using shared memory to implement co-located RPC significantly improves both communication throughput and latency by avoiding data structure serialization.