2010
DOI: 10.1080/00051144.2010.11828394
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Integrating Streaming Computations for Efficient Execution on Novel Multicore Architectures

Abstract: Original scientific paperStreaming has emerged as an important model in present-day applications, ranging from multimedia to scientific computing. Moreover, the emergence of new multicore architectures has resulted with new challenges in efficient utilization of available computational resources. Streaming model offers the portability and scalability of performance with the increasing number of cores. In this paper we propose a tool which enables the implementation of the compute-intensive stream processing ke… Show more

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Cited by 4 publications
(4 citation statements)
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“…We improve the execution performance of CBPC utilizing the streaming model of computation and expressing compute intensive part of the algorithm in the StreamIt programming language. Following the observations from our previous work on integrating streaming computations we modified our experimental tool reported in [15], which resulted in STREAMGATE interface and runtime. The main purpose of the interface is to provide existing applications the easy way to integrate high-level and optimized streaming computations as reusable kernels.…”
Section: Streaming Implementation Of Cbpcmentioning
confidence: 99%
See 1 more Smart Citation
“…We improve the execution performance of CBPC utilizing the streaming model of computation and expressing compute intensive part of the algorithm in the StreamIt programming language. Following the observations from our previous work on integrating streaming computations we modified our experimental tool reported in [15], which resulted in STREAMGATE interface and runtime. The main purpose of the interface is to provide existing applications the easy way to integrate high-level and optimized streaming computations as reusable kernels.…”
Section: Streaming Implementation Of Cbpcmentioning
confidence: 99%
“…Additionally, our intention was to enable the portability among different architectures, from symmetric multicores with shared memory to heterogeneous multiprocessor architectures which rapidly emerge in the embedded computing devices. In order to end up with a scalable and portable implementation we exploit streaming compilation infrastructure that we described previously in [15], which we further extended in order to generate reusable streaming kernels in the form of static library. This approach enabled us to obtain scalable performance improvement in regard to increasing the number of processing cores without any modifications to existing source.…”
Section: Introductionmentioning
confidence: 99%
“…Since the release of the first generation dual-core processor by IBM in 2001, Sun in 2004, and AMD in 2005, more and more cores are built into a single processor with the development of multicore technology [11]. Multi-core architectures are today's dominant computing platforms [12,13]. Parallel architectures and programming models are not independent.…”
Section: Introductionmentioning
confidence: 99%
“…Our approach is based on a functional decomposition of existing (non-parallelized) application or a newly designed application, where the most compute-intensive elements are (re)designed and (re)implemented in the streaming domain, whereas non-critical elements are left/implemented in the sequential domain. The streaming domain part of the application is implemented using StreamIt language [7], while the bridge between the streaming and the sequential domain is provided and managed by STREAMGATE interface and run-time [8].…”
Section: Introductionmentioning
confidence: 99%