The CCA component model for high-performance scientific computing

Computing Research Repository, 2005

The COmputational MODule Integrator (COMODI) [1] is an initiative aiming at a component based framework, component developer tool and component repository for scientific computing. We identify the main ingredients to a solution that would be sufficiently appealing to scientists and engineers to consider alternatives to their deeply rooted programming traditions. The overall structure of the complete solution is sketched with special emphasis on the Component Developer Tool standing at the basis of COMODI.

Ninth International Workshop on High-Level Parallel Programming Models and Supportive Environments, 2004. Proceedings., 2004

We present an overview of the SCIRun2 parallel component framework. SCIRun2 is based on the Common Component Architecture (CCA) and the SCI Institutes' SCIRun[10]. SCIRun2 supports distributed computing through distributed objects. Parallel components are managed transparently over an MxN method invocation and data redistribution subsystem. A meta component model based on CCA is used to accommodate multiple component models such as CCA, CORBA and Dataflow. A group of monitoring components built on top of the TAU toolkit[13] evaluate the performance of the other components.

Proceedings of GECO- …

High Performance Computing–HiPC …, 2005

2000

The use of component architectures to solve the problem of reuse and interoperability in scientific computing has been investigated by various research groups during the last years. Moreover, architectures for Internet accessible math- ematical services have been proposed. In this paper give a brief abstract require- ments analysis with respect to these problems and show that there is an existing

The ever-increasing complexity of modern high-performance scientific simulation software presents a tremendous challenge to the development and use of this type of software, with significant impacts on productivity. Component-based software engineering is a means of addressing complexity that has been developed primarily in response to the needs of business and related software environments, but which has not yet had a significant impact on high-end computing. In this paper, we present the Common Component Architecture (CCA) as a com-ponent model designed to meet the special needs of high-performance scientific computing, focusing on how the CCA addresses issues of complexity. Unique among component architectures is the technique presented here by which a CCA component can act as a container to encapsulate and control other components without itself having to implement the functionality of a framework.

Lecture Notes in Computer Science, 2006

Commercial component-based software engineering practices, such as the CORBA component model, Enterprise JavaBeans, and COM, are well-established in the business computing community. These practices present an approach for managing the increasing complexity of scientific software development, which has motivated the Common Component Architecture (CCA), a component specification targeted at highperformance scientific application development. The CCA is an approach to component development that is minimal in terms of the complexity of component interface requirements and imposes a minimal performance penalty. While this lightweight specification has enabled the development of a number of high-performance scientific components in several domains, the software design process for developing component-based scientific codes is not yet well defined. This fact, coupled with the fact that component-based approaches are still new to the scientific community, may lead to an ad hoc design process, potentially resulting in code that is harder to maintain, extend, and test and may negatively affect performance. We explore some concepts and approaches based on widely accepted software architecture design principles and discuss their potential application in the development of high-performance scientific component applications. We particularly emphasize those principles and approaches that contribute to making CCA-based applications easier to design, implement, and maintain, as well as enabling dynamic adaptivity with the goal of maximizing performance.

2001

The idea of using component frameworks to deal with the complexity of developing interdisciplinary HPC applications is becoming increasingly popular. Such systems enable programmers to accelerate project development through introducing higher level abstractions and allowing code reusability, as well as provide clearly specified component interfaces which facilitate the task of team interaction. These potential benefits has encouraged research groups within a number of laboratories and universities to develop, and experiment with prototype systems. Consequently, there is a need for an interoperablity standard. The need for component programming has been recognized by the business world and resulted in the development of systems such as Microsoft COM, the new Corba Component Model (CCM), Enterprise Java Beans and others. However, these systems were designed primarily for sequential applications and do not address the needs of HPC. Their most important shortcoming from the point of view of HPC is that they don't support abstractions necessary for high-performance, parallel programming, and don't stress enough what is often the most important factor in scientific programming: performance. In addition, the existing systems are often invasive, that is, they require substantial modifications to existing applications which may not be acceptable to the developer of high-performance components. In view of these problems it is critical to develop a standard which will address specifically the needs of HPC community. To this end, we embarked a collaboration with

International Journal of High Performance Computing Applications, 2006

The Common Component Architecture (CCA) provides a means for software developers to manage the complexity of large-scale scientific simulations and to move toward a plug-and-play environment for high-performance computing. In the scientific computing context, component models also promote collaboration using independently developed software, thereby allowing particular individuals or groups to focus on the aspects of greatest interest to them. The CCA supports parallel and distributed computing as well as local high-performance connections between components in a language-independent manner. The design places minimal requirements on components and thus facilitates the integration of existing code into the CCA environment. The CCA model imposes minimal overhead to minimize the impact on application performance. The focus on high performance distinguishes the CCA from most other component models. The CCA is being applied within an increasing range of disciplines, including combustion research, global climate simulation, and computational chemistry.

Proceedings International Parallel and Distributed Processing Symposium, 2003

This work targets the emerging use of software component technology for high-performance scientific parallel and distributed computing. While component software engineering will benefit the construction of complex science applications,