Abstract
Heterogeneous Reconfigurable MPSoCs, coupling microprocessors with Programmable Logic, are becoming extremely important in High-Performance Embedded Computing domain where energy consumption is a key factor to be considered by every designer. However, efficient hardware/software co-design still requires experience and a big effort: finding an optimal solution and an acceptable trade-off between performance and energy may require several tests and it is strongly platform-dependent. To this respect, a Dataflow-based method is used in this work for exploring different hardware/software configurations (number of hardware accelerators and FPGA frequency). As a use case, the acceleration of a well-known 3D video game (DOOM) is presented. The method offers rapid trade-off analysis in terms of non-functional parameters such as computing performance or power/energy measurements.
Extensive experimental results show that is possible to speed up the game and, at the same time, reduce the energy consumption of the whole platform. A custom Linux-based Operating System for Zynq Ultrascale+ was created, including a GPU driver to support a graphical interface on an HDMI screen and drivers to manage custom hardware accelerators on the FPGA side.
The best solution to save up to 63% of energy corresponds to the use of four parallel hardware accelerators, where a function speed up of x3.6 and an application speed up of x2 (in line with Amdahl’s law) is obtained.
Additionally, a set of Pareto optimal solutions are reported in the results section.
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The hack comes from the Xilinx’s documentation: “SDSoC Environment Platform Development Guide UG1146 (v2017.4) January 26, 2018” and was adapted for our purpose. In the document, it is used with Petalinux. However, the use of Petalinux is avoided in this work.
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This work was supported by the Spanish Ministry (Ministerio de Economía y Competitividad) under projects PLATINO under Grant TEC2012-31145.
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Suriano, L., Lima, D., de la Torre, E. (2020). Accelerating a Classic 3D Video Game on Heterogeneous Reconfigurable MPSoCs. In: Rincón, F., Barba, J., So, H., Diniz, P., Caba, J. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2020. Lecture Notes in Computer Science(), vol 12083. Springer, Cham. https://doi.org/10.1007/978-3-030-44534-8_11
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