This paper describes the semantics of Quantum, a language that was specifically designed to control resource consumption of distributed computations, such as mobile agent style applications. In Quantum, computations can be driven by mastering their resource consumption. Resources can be understood as processors cycles, geographical expansion, bandwidth or duration of communications, etc. We adopt a generic view by saying that computations need energy to be performed. Quantum relies on three new primitives that deal with energy. The first primitive creates a tank of energy associated with a computation. Asynchronous notifications inform the user of energy exhaustion and computation termination. The other two primitives allow us to implement suspension and resumption of computations by emptying a tank and by supplying more energy to a tank. The semantics takes the form of an abstract machine with explicit parallelism and energy-related primitives. 1 Introduction Millions of computers ...

. The remote service request, a form of remote procedure call, and the global pointer, a global naming mechanism, are two features at the heart of Nexus, a library for building distributed systems. NeXeme is an extension of Scheme that fully integrates both concepts in a mostly-functional framework, hence providing an expressive language for distributed computing. This paper presents a semantics for this Scheme extension, and also describes a NeXeme implementation, including its distributed garbage collector. 1 Introduction Scheme [20] is a mostly-functional language, i.e., it is a fully functional language that also supports imperative notions such as assignments and continuations, for efficiency and expressivity reasons. We believe that a distributed extension of such a language requires a mechanism to invoke functions remotely, so that distribution becomes part of the most fundamental operation of the language. Such an approach is also adopted by languages such as Obliq [2], Java +...

We have recently defined a new algorithm for distributed garbage collection based on reference-counting [20, 24]. At the heart of the algorithm, we find tree rerooting, a mechanism able to reduce third-party dependencies by reorganising diffusion trees. In reality, the algorithm describes a spectrum of algorithms according to the policy used to manage messages. In this paper, we present the implementation of the algorithm and evaluate its performance. We have implemented two policies, which are extremes of the spectrum, respectively using and not using tree rerooting. In addition, two different strategies for managing action queues have been implemented. The conclusions of our experimentations are the following. Tree rerooting offers more parallelism during distributed gc activity; we explain this phenomenon by the length reduction of causality chains in the distributed gc. Grouping messages per destination dramatically reduces the number of messages, but requires a more complex implementation as messages have to be sorted per destination. Speed up of 100% has been observed on some benchmarks.

Millions of computers are now connected together by the Internet. At a fast pace, applications are taking advantage of these new capabilities, and are becoming parallel and distributed, e.g. applets on the WWW or agent technology. As we live in a world with finite resources, an important challenge is to be able to control computations in such an environment. For instance, a user might like to suspend a computation because another one seems to be more promising. In this paper, we present a paradigm that allows the programmer to monitor and control computations, whether parallel or distributed, by mastering their resource consumption. We describe an implementation on top of the thread library PPCR and the message-passing library Nexus. 1 Introduction As we live in a world with finite resources, it is of paramount importance for the user to be able to monitor and control computations. This task is all the more complex since computations may be parallel, distributed, and most probably ma...

this paper, we study how linking mechanisms contribute to the expressiveness of

. Coordination languages for parallel and distributed systems specify mechanisms for creating tasks and communicating data among them. These languages typically assume that (a) once a task begins execution on some processor, it will remain resident on that processor throughout its lifetime, and (b) communicating shared data among tasks is through some form of message-passing and data migration. In this paper, we investigate an alternative approach to understanding coordination. Communication-passing style (CmPS) refers to a coordination semantics in which data communication is always undertaken by migrating the continuation of the task requiring the data to the processor where the data resides. Communication-passing style is closely related to continuation-passing style (CPS), a useful transformation for compiling functional languages. Just as CPS eliminates implicit call-return sequences, CmPS eliminates implicit inter-processor data communication and synchronization reque...

Millions of computers are now connected together by the Internet. At a fast pace, applications are taking profit of these new capabilities, and become parallel and distributed, e.g. applets on the WWW or agent technology. As we live in a world with finite resources, an important challenge is to be able to control computations in such an environment. For instance, a user might like to suspend a computation because another one seems to be more promising. In this paper, we present a paradigm that allows the programmer to monitor and control computations, whether parallel or distributed, by mastering their resource consumption.

As computers are deployed in increasingly diverse, numerous, and critical roles, the need for confidence in their hardware and software becomes more acute. Often, however, computer technologies, such as programming languages, lack a sufficiently formal definition to allow rigorous mathematical analysis of their properties. Even in cases where a formal definition is available, the theorems to be proven and the definition itself tend to have many cases and many details that are easily overlooked when writing a proof by hand. This has created interest in the mechanization of the proof process through the use of automated proof assistants. In this report, we develop a formal definition for a programming language called IntegerPython, which is a subset of the Python language that supports integers, booleans, global variables, loops, modules, and nested functions. The definition takes the form of an operational semantics on a CEKS machine, which we embed in the Isabelle/HOL mechanized logic. We then prove an invariant of the CEKS machine in Isabelle/HOL. The report concludes with strategies for the efficient, executable implementation of the IntegerPython semantics and its extension into a semantics of