Browsing by Subject "Domain specific language"

Now showing 1 - 4 of 4

Open Access
Architecture framework for mapping parallel algorithms to parallel computing platforms
(CEUR-WS, 2013) Tekinerdogan, Bedir; Arkin, E.
Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, and the mapping of the algorithm to the logical configuration platform. Unfortunately, in current parallel computing approaches there does not seem to be precise modeling approaches for supporting the mapping process. The lack of a clear and precise modeling approach for parallel computing impedes the communication and analysis of the decisions for supporting the mapping of parallel algorithms to parallel computing platforms. In this paper we present an architecture framework for modeling the various views that are related to the mapping process. An architectural framework organizes and structures the proposed architectural viewpoints. We propose five coherent set of viewpoints for supporting the mapping of parallel algorithms to parallel computing platforms. We illustrate the architecture framework for the mapping of array increment algorithm to the parallel computing platform. Copyright © 2013 for the individual papers by the papers' authors.
Open Access
Domain specific language for deployment of parallel applications on parallel computing platforms
(Association for Computing Machinery, 2014-08) Arkın, E.; Tekinerdoğan, Bedir
To increase the computing performance the current trend is towards applying parallel computing in which parallel tasks are executed on multiple nodes. The deployment of tasks on the computing platform usually impacts the overall performance and as such needs to be modelled carefully. In the architecture design community the deployment viewpoint is an important viewpoint to support this mapping process. In general the derived deployment views are visual notations that are not amenable for run-time processing, and do not scale well for deployment of large scale parallel applications. In this paper we propose a domain specific language (DSL) for modeling the deployment of parallel applications and for providing automated support for the deployment process. The DSL is based on a metamodel that is derived after a domain analysis on parallel computing. We illustrate the application of the DSL for a traffic simulation system and provide a set of important scenarios for using the DSL. © 2014 ACM.
Open Access
From a calculus to an execution environment for stream processing
(ACM, 2012) Soulé, R.; Hirzel, M.; Gedik, Buğra; Grimm, R.
At one level, this paper is about River, a virtual execution environment for stream processing. Stream processing is a paradigm well-suited for many modern data processing systems that ingest high-volume data streams from the real world, such as audio/video streaming, high-frequency trading, and security monitoring. One attractive property of stream processing is that it lends itself to parallelization on multicores, and even to distribution on clusters when extreme scale is required. Stream processing has been co-evolved by several communities, leading to diverse languages with similar core concepts. Providing a common execution environment reduces language development effort and increases portability. We designed River as a practical realization of Brooklet, a calculus for stream processing. So at another level, this paper is about a journey from theory (the calculus) to practice (the execution environment). The challenge is that, by definition, a calculus abstracts away all but the most central concepts. Hence, there are several research questions in concretizing the missing parts, not to mention a significant engineering effort in implementing them. But the effort is well worth it, because using a calculus as a foundation yields clear semantics and proven correctness results. Copyright © 2012 ACM.
Open Access
Model-driven transformations for mapping parallel algorithms on parallel computing platforms
(MDHPCL, 2013) Arkin, E.; Tekinerdoğan, Bedir
One of the important problems in parallel computing is the mapping of the parallel algorithm to the parallel computing platform. Hereby, for each parallel node the corresponding code for the parallel nodes must be implemented. For platforms with a limited number of processing nodes this can be done manually. However, in case the parallel computing platform consists of hundreds of thousands of processing nodes then the manual coding of the parallel algorithms becomes intractable and error-prone. Moreover, a change of the parallel computing platform requires considerable effort and time of coding. In this paper we present a model-driven approach for generating the code of selected parallel algorithms to be mapped on parallel computing platforms. We describe the required platform independent metamodel, and the model-to-model and the model-to-text transformation patterns. We illustrate our approach for the parallel matrix multiplication algorithm. Copyright © 2013 for the individual papers by the papers' authors.