COM and DCOM: Microsoft's vision for distributed objects
COM and DCOM: Microsoft's vision for distributed objects
Multimethod communication for high-performance metacomputing applications
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Building a World-Wide virtual machine based on web and HPCC technologies
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
PARDIS: CORBA-based architecture for application-level parallel distributed computation
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
The design and evaluation of a virtual distributed computing environment
Cluster Computing
IPPS '99/SPDP '99 Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Customized Dynamic Load Balancing for a Network of Workstations
Customized Dynamic Load Balancing for a Network of Workstations
A Synopsis of the Legion Project
A Synopsis of the Legion Project
Requirements for and evaluation of RMI protocols for scientific computing
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Inflation and deflation of self-adaptive applications
Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems
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Development of high-performance distributed applications, called metaapplications, is extremely challenging because of their complex runtime environment coupled with their requirements of high-performance and Quality of Service (QoS). Such applications typically run on a set of heterogeneous machines with dynamically varying loads, connected by heterogeneous networks possibly supporting a wide variety of communication protocols. In spite of the size and complexity of such applications, they must provide the high-performance and QoS mandated by their users. In order to achieve the goal of high-performance, they need to adaptively utilize their computational and communication resources. Apart from the requirements of adaptive resource utilization, such applications have a third kind of requirement related to remote access QoS. Different clients, although accessing a single server resource, may have differing QoS requirements from their remote connections. A single server resource may also need to provide different QoS for different clients, depending on various issues such as the amount of trust between the server and a given client. These QoS requirements can be encapsulated under the abstraction of remote access capabilities. Metaapplications need to address all the above three requirements in order to achieve the goal of high-performance and satisfy user expectations of QoS. This paper presents Open HPC++, a programming environment for high-performance applications running in a complex and heterogeneous run-time environment. Open HPC++ provides application level tools and mechanisms to satisfy application requirements of adaptive resource utilization and remote access capabilities. Open HPC++ is designed on the lines of CORBA and uses an Object Request Broker (ORB) to support seamless communication between distributed application components. In order to provide adaptive utilization of communication resources, it uses the principle of open implementation to open up the communication mechanisms of its ORB. By virtue of its open architecture, the ORB supports multiple, possibly custom, communication protocols, along with automatic and user controlled protocol selection at run-time. An extension of the same mechanism is used to support the concept of remote access capabilities. In order to support adaptive utilization of computational resources, Open HPC++ also provides a flexible yet powerful set of load-balancing mechanisms that can be used to implement custom load-balancing strategies. The paper also presents performance evaluations of Open HPC++ adaptivity and load-balancing mechanisms.