The Movidius Myriad Architecture´s Potential for Scientific Computing

In recent years, a new generation of ultralow-power processors have emerged that are aimed primarily at signal processing in mobile computing. However, their architecture could make some of these useful for other applications. Algorithms originally developed for scientific computing are used increasingly in signal conditioning and emerging fields such as computer vision, increasing the demand for computing power in mobile systems. In this article, the authors describe the design and implementation of dense matrix multiplication on the Movidius Myriad architecture and evaluate its performance and energy efficiency. The authors demonstrate a performance of 8.11 Gflops on the Myriad I processor and a performance/watt ratio of 23.17 Gflops/W for a key computational kernel. These results show significant potential for scientific-computing tasks and invite further research.