RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

Actor Garbage Collection Using Vertex-Preserving Actor-to-Object Graph Transformations

Abstract. Large-scale distributed computing applications require concurrent programming models that support modular and compositional software development. The actor model supports the development of independent software components with its asynchronous message-passing communication and state encapsulation properties. Automatic actor garbage collection is necessary for high-level actor-oriented programming, but identifying live actors is not as intuitive and easy as identifying live passive objects in a reference graph. However, a transformation method can turn an actor reference graph into a passive object reference graph, which enables the use of passive object garbage collection algorithms and simplifies the problem of actor garbage collection. In this paper, we formally define potential communication by introducing two binary relations- the may-talk-to and the may-transitively-talk-to relations, which are then used to define the set of live actors. We also devise two vertexpreserving transformation methods to transform an actor reference graph into a passive object reference graph. We provide correctness proofs for the proposed algorithms. The experimental results also show that the proposed algorithms are efficient