Abstract-State-of-the-art mobile system-on-chips (SoC) include heterogeneity in various forms for accelerated and energyefficient execution of diverse range of applications. The modern SoCs now include programmable cores such as CPU and GPU with very different functionality. The SoCs also integrate performance heterogeneous cores with different power-performance characteristics but the same instruction-set architecture such as ARM big.LITTLE. In this paper, we first explore and establish the combined benefits of functional heterogeneity and performance heterogeneity in improving power-performance behavior of data parallel applications. Next, given an application specified in OpenCL, we present a static partitioning strategy to execute the application kernel across CPU and GPU cores along with voltage-frequency setting for individual cores so as to obtain the best power-performance tradeoff. We achieve over 19% runtime improvement by exploiting the functional and performance heterogeneities concurrently. In addition, energy saving of 36% is achieved by using appropriate voltage-frequency setting without significantly degrading the runtime improvement from concurrent execution.
This enables concurrent use of CPU and GPU to execute an application threads, but in REF , a static partitioning is performed by using all the CPU and GPU cores.
Energy-efficient execution of data-parallel applications on heterogeneous mobile platforms
2015 33rd IEEE International Conference on Computer Design (ICCD)
2015 33rd IEEE International Conference on Computer Design (ICCD)
Computer Science