Abstract
Three parallel sorting applications and two list output protocols for the first phase of an external sort execute on a fine-grained many-core processor array that contains no algorithm-specific hardware acting as a co-processor with a variety of array sizes. Results are generated using a cycle-accurate model based on measured data from a fabricated many-core chip, and simulated for different processor array sizes. The data shows most energy efficient first-phase many-core sort requires over 65× lower energy than GNU C++ standard library sort performed on an Intel laptop-class processor and over 105× lower energy than a radix sort running on an Nvidia GPU. In addition, the highest first-phase throughput many-core sort is over 9.8× faster than the std::sort and over 14× faster than the radix sort. Both phases of a 10 GB external sort require 6.2× lower energy×time energy delay product than the std::sort and over 13× lower energy×time than the radix sort.
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