PAMGUARD is open-source, platform-independent software to address the needs of developers and users of Passive Acoustic Monitoring (PAM) systems. For the PAM operator—marine mammal biologist, manager, or mitigator—PAMGUARD provides a flexible and easy-to-use suite of detection, localization, data management, and display modules. These provide a standard interface across different platforms with the flexibility to allow multiple detectors to be added, removed, and configured according to the species of interest and the hardware configuration on a particular project. For developers of PAM systems, an Application Programming Interface (API) has been developed which contains standard classes for the efficient handling of many types of data, interfaces to acquisition hardware and to databases, and a GUI framework for data display. PAMGUARD replicates and exceeds the capabilities of earlier real time monitoring programs such as the IFAW Logger Suite and Ishmael. Ongoing developments include improved real-time location and automated species classification. [PAMGUARD funded by the OGP E&P Sound and Marine Life project.]

The process of writing large parallel programs is complicated by the need to specify both the parallel behaviour of the program and the algorithm that is to be used to compute its result. This paper introduces evaluation strategies: lazy higher-order functions that control the parallel evaluation of non-strict functional languages. Using evaluation strategies, it is possible to achieve a clean separation between algorithmic and behavioural code. The result is enhanced clarity and shorter parallel programs. Evaluation strategies are a very general concept: this paper shows how they can be used to model a wide range of commonly used programming paradigms, including divide-and-conquer parallelism, pipeline parallelism, producer/consumer parallelism, and data-oriented parallelism. Because they are based on unrestricted higher-order functions, they can also capture irregular parallel structures. Evaluation strategies are not just of theoretical interest: they have evolved out of our experience in parallelising several large-scale parallel applications, where they have proved invaluable in helping to manage the complexities of parallel behaviour. Some of these applications are described in detail here. The largest application we have studied to date, Lolita, is a 40,000 line natural language engineering system. Initial results show that for these programs we can achieve acceptable parallel performance, for relatively little programming effort.

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Massively Multiplayer Online Games (MMOGs) are increasing in both popularity and scale, and while classical Client/Server (C/S) architectures convey some benefits, they suffer from significant technical and commercial drawbacks. This realisation has sparked intensive research interest in adapting MMOGs to Peer-to-Peer (P2P) architectures. This paper articulates a comprehensive set of six design issues to be addressed by P2P MMOGs, namely Interest Management (IM), game event dissemination, Non-Player Character (NPC) host allocation, game state persistency, cheating mitigation and incentive mechanisms. Design alternatives for each issue are systematically compared, and their interrelationships discussed. We further evaluate how well representative P2P MMOG architectures fulfil the design criteria.