Core Grid technologies are rapidly maturing, but there remains a shortage of real Grid applications. One important reason is the lack of a simple and high-level application programming toolkit, bridging the gap between existing Grid middleware and application-level needs. The Grid Application Toolkit (GAT), as currently developed by the EC-funded project GridLab [1], provides this missing functionality. As seen from the application, the GAT provides a unified simple programming interface to the Grid infrastructure, tailored to the needs of Grid application programmers and users. A uniform programming interface will be needed for application developers to create a new generation of "Grid-aware" applications. The GAT implementation handles both the complexity and the variety of existing Grid middleware services via so-called adaptors. Complementing existing Grid middleware, GridLab also provides high-level services to implement the GAT functionality.We present the GridLab software architecture, consisting of the GAT, environment-specific adaptors, and GridLab services. We elaborate the concepts underlying the GAT and outline the corresponding application programming interface. We present the functionality of GridLab's high-level services and demonstrate how a dynamic Grid application can easily benefit from the GAT. All GridLab software is open source and can be downloaded from the project Web site.

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This paper describes innovative architectures and techniques for reserving and coordinating highly distributed resources, a capability required for many large scale applications. In the fall of 2006, Japan's G-lambda research team and the United States' EnLIGHTened Computing research team used these innovations to achieve the world's first inter-domain coordination of resource managers for in-advance reservation of network bandwidth and compute resources between and among both the US and Japan. The compute and network resource managers had different interfaces and were independently developed. Automated interoperability among the resources in both countries was enabled through various Grid middleware components. In this paper, we describe the middleware components, testbeds, results, and lessons learned.