Abstract
It is a challenging issue whether scientific applications are suitable for Imagine architecture. To address this problem, this paper presents a novel architecture-based optimization for the key techniques of mapping scientific applications to Imagine. Our specific contributions include that we achieve fine kernel granularity and choose necessary arrays to organize appropriate streams. Specially, we develop a new stream program generation algorithm based on the architecture-based optimization. We implement our algorithm to some representative scientific applications on ISIM simulation of Imagine, compared the corresponding FORTRAN programs running on Itanium 2. The experimental results show that the optimizing stream programs can efficiently improve computational intensiveness, enhance locality of LRF and SRF, avoid index stream overhead and enable parallelism to utilize ALUs. It is certain that Imagine is efficient for many scientific applications.
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Du, J., Yang, X., Wang, G., Tang, T., Zeng, K. (2007). Architecture-Based Optimization for Mapping Scientific Applications to Imagine. In: Stojmenovic, I., Thulasiram, R.K., Yang, L.T., Jia, W., Guo, M., de Mello, R.F. (eds) Parallel and Distributed Processing and Applications. ISPA 2007. Lecture Notes in Computer Science, vol 4742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74742-0_6
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DOI: https://doi.org/10.1007/978-3-540-74742-0_6
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