Abstract
The competition for higher performance/price ratio is pushing processor chip design into the manycore age. Existing multicore technologies such as caching no longer scale up to dozens of processor cores. Even moderate level of performance optimisation requires direct handling of data locality and distribution. Such architectural complexity inevitably introduces challenges to programming. A better approach for abstraction than completely relying on compiler optimization is to expose some performance-critical features of the system and expect the programmer to handle them explicitly. This paper studies an algebra-semantic programming theory for a performance-transparent level of parallel programming of array-based data layout, distribution, transfer and their affinity with threads. The programming model contributes to the simplification of system-level complexities and the answering of crucial engineering questions through rigorous reasoning.
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Chen, Y. (2013). Algebraic Program Semantics for Supercomputing. In: Liu, Z., Woodcock, J., Zhu, H. (eds) Theories of Programming and Formal Methods. Lecture Notes in Computer Science, vol 8051. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39698-4_8
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DOI: https://doi.org/10.1007/978-3-642-39698-4_8
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