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No abstract

Safepoints are a virtual machine mechanism that allows one thread to suspend other threads in a known state so that runtime actions can be performed without interruption and with data structures in a consistent state. Many virtual machines use safepoints as a mechanism to provide services such as stop-the-world garbage collection, debugging, and modification to running code such as installing or replacing classes. Languages implemented on these virtual machines may have access to these services, but not directly to the safepoint mechanism itself. We show that safepoints have many useful applications for the implementation of guest languages running on a virtual machine. We describe an API for using safepoints in languages that were implemented under the Truffle language implementation framework on the Java Virtual Machine and show several applications of the API to implement useful guest-language functionality. We present an efficient implementation of this API, when running in combination with the Graal dynamic compiler. We also demonstrate that our safepoints cause zero overhead with respect to peak performance and statistically insignificant overhead with respect to compilation time. We compare this to other techniques that could be used to implement the same functionality and demonstrate the large overhead that they incur.

Dynamic programming languages such as Python and Ruby are widely used, and much effort is spent on making them efficient. One substantial research effort in this direction is the enabling of parallel code execution. While there has been significant progress, making dynamic collections efficient, scalable, and thread-safe is an open issue. Typical programs in dynamic languages use few but versatile collection types. Such collections are an important ingredient of dynamic environments, but are difficult to make safe, efficient, and scalable. In this paper, we propose an approach for efficient and concurrent collections by gradually increasing synchronization levels according to the dynamic needs of each collection instance. Collections reachable only by a single thread have no synchronization, arrays accessed in bounds have minimal synchronization, and for the general case, we adopt the Layout Lock paradigm and extend its design with a lightweight version that fits the setting of dynamic languages. We apply our approach to Ruby's Array and Hash collections. Our experiments show that our approach has no overhead on single-threaded benchmarks, scales linearly for Array and Hash accesses, achieves the same scalability as Fortran and Java for classic parallel algorithms, and scales better than other Ruby implementations on Ruby workloads. CCS Concepts: • Software and its engineering → Data types and structures; Concurrent programming structures; Dynamic compilers;

The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.