Abstract
Current microprocessors contain SIMD execution units (also called multimedia or vector extensions) that allow the data-parallel execution of operations on several subwords packed in 64-bit or 128-bit registers. They can accelerate not only typical multimedia applications but also many other algorithms based on vector and matrix operations. In this paper the results of a detailed experimental study about the suitability of such units for the fast simulation of neural networks are presented. It is shown that a speedup in the range from 2.0 to 8.6 compared to sequential implementations can be achieved. A performance counter analysis is provided to explain several effects by features of the processor architecture.
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