Standby efficiency for connected devices is one of the priorities of the G20’s Energy Efficiency Action Plan. We propose transparent programming language mechanisms to enforce that applications remain in the deepest standby modes for the longest periods of time. We extend the programming language Céu with support for interrupt service routines and with a simple power management runtime. Based on these primitives, we also provide device drivers that allow applications to take advantage of standby automatically. Our approach relies on the synchronous semantics of the language which guarantees that reactions to the environment always reach an idle state amenable to standby. In addition, in order to lower the programming barrier of adoption, we show that programs in Céu can keep a sequential syntactic structure, even when applications require non-trivial concurrent behavior.

DistributedCL is a middleware which enables transparent parallel processing on distributed GPUs. With the support of the DistributedCL middleware an application designed to use the OpenCL API can run in a distributed manner and transparently use remote GPUs without having to change or rebuild the code. The proposed architecture for the DistributedCL middleware is modular, with well-defined layers. A prototype was built according to the architecture, which considered various optimization points, including sending data in batches, network asynchronous communication and asynchronous request to the OpenCL API. The prototype was evaluated using available benchmarks and a specific benchmark, the CLBench, was developed to facilitate the evaluations according to the amount of processed data. The prototype presented good performance, higher when compared to similar proposals, which also consider transparent use of remote GPUs. The data size to be transmitted over the network was the major limiting factor.

Abstract Resource management is an important aspect to consider regarding applications that might have different non‐functional or operational requirements, when running in distributed and heterogeneous environments. In this context, it is necessary to provide the means to specify the required resource constraints and an infrastructure that can adapt the applications in light of the changes in resource availability. We adopted a contract‐based approach to describe and maintain parallel applications that have non‐functional requirements in a Computing Grid context, called ZeliGrid. To form the supporting infrastructure we have designed a software architecture that integrates some of the Globus services, the LDAP and the NWS monitoring services. Some modules that map the contract approach into software artifacts were also integrated to this architecture. This paper addresses the architecture and integration issues of our approach, as well as how we put the pieces together highlighting deployment and implementation details, which have to consider diverse aspects such as monitoring, security and dynamic reconfiguration. Copyright © 2010 John Wiley & Sons, Ltd.