In a distributed grid environment with ambitious service demands the job submission and management interfaces provide functionality of major importance. Emerging e-science and grid infrastructures such as EGEE and DEISA rely on highly available services that are capable of managing scientific jobs. It is the adoption of emerging open standard interfaces which allows the distribution of grid resources in such a way that their actual service implementation or grid technologies are not isolated from each other, especially when these resources are deployed in different e-science infrastructures that consist of different types of computational resources. This paper motivates the interoperability of these infrastructures and discusses solutions. We describe the adoption of various open standards that recently emerged from the open grid forum (OGF) in the field of job submission and management by well-known grid technologies, respectively gLite and UNICORE. This has a fundamental impact on the interoperability between these technologies and thus within the next generation e-science infrastructures that rely on these technologies.

Many existing Grid technologies and resource management systems lack a standardized job submission interface in Grid environments or e-Infrastructures. Even if the same language for job description is used, often the interface for job submission is also different in each of these technologies. The evolvement of the standardized Job Submission and Description Language (JSDL) as well as the OGSA - Basic Execution Services (OGSA-BES) pave the way to improve the interoperability of all these technologies enabling cross-Grid job submission and better resource management capabilities. In addition, the BytelO standards provide useful mechanisms for data access that can be used in conjunction with these improved resource management capabilities. This paper describes the integration of these standards into the recently released UNICORE 6 Grid middleware that is based on open standards such as the Web Services Resource Framework (WS-RF) and WS-Addressing (WS-A).

Massively parallel programs generally use memory on a vast scale, compared with sequential programs. Indeed, performance seems to 'trade-off' against memory use. Hence, regulation of memory use, via control of the workload, is a fundamental requirement in a massively parallel computer system. Moreover, this must be achieved with a minimum of disruption to the performance of its massively parallel computations. This paper investigates how this has been achieved in the Manchester Data-Flow Computing System, which is based on an experimental, fine-grain massively parallel computer architecture that has been extensively developed over the last fifteen years. The design and performance of the Throttle Unit, which is the device responsible for managing the workload in this system, are presented and analysed.

The Manchester Data-Flow Machine, MDFM, has evolved continuously during the past decade. By the time the prototype uniprocessor hardware system was decommissioned, in 1989, the putative multi-processor architecture comprised separate Processing Elements and Structure Store Units, together with a “global” Allocator and Throttle Unit, all linked by a packet-based Interconnection Switch.