Dynamic Application Reconfiguration on Heterogeneous Hardware

Published in VEE 2019, Providence, Rhode Island, United States, 2019

Recommended citation: Juan Fumero, Michail Papadimitriou, Foivos S. Zakkak, Maria Xekalaki, James Clarkson, and Christos Kotselidis. 2019. Dynamic application reconfiguration on heterogeneous hardware. In Proceedings of the 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE 2019). ACM, New York, NY, USA, 165-178. DOI: https://doi.org/10.1145/3313808.3313819 https://github.com/jjfumero/jjfumero.github.io/blob/master/files/VEE2019_Fumero_Preprint.pdf


Authors: Juan Fumero, Michail Papadimitriou, Foivos Zakkak, Maria Xekalaki, James Clarkson, Christos Kotselidis.

By utilizing diverse heterogeneous hardware resources, developers can significantly improve the performance of their applications. Currently, in order to determine which part1s of an application suit a particular type of hardware accelerator better, an offline analysis that uses a priori knowledge of the target hardware configuration is necessary. To make matters worse, the above process has to be repeated every time the application or the hardware configuration changes.

This paper introduces TornadoVM, a virtual machine capable of reconfiguring applications, at run-time, for hardware acceleration based on the currently available hardware resources. Through TornadoVM, we introduce a new level of compilation in which applications can benefit from heterogeneous hardware. We showcase the capabilities of TornadoVM by executing a complex computer vision application and six benchmarks on a heterogeneous system that includes a CPU, an FPGA, and a GPU. Our evaluation shows that by using dynamic reconfiguration, we achieve an average of 7.7× speedup over the statically-configured accelerated code.