High-Performance Computing on a Honeycomb Architecture
نویسندگان
چکیده
We explore time and space optimization problems involved in the mapping of parallel algorithms onto a honeycomb architecture. When a well-known mapping is used, mapped algorithms generally exhibit execution slowdown and require too large area. We design several optimization techniques and enhance the mapping process. Experimental results show more than 50 % saving in processor resources and 30 % saving in execution time, on average. Since computing performances are improved, also the applicability of the honeycomb architecture is wider.
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