This dataset supports the article entitled "Energy-Efficient Run-time Mapping and Thread Partitioning of Concurrent OpenCL Applications on CPU-GPU MPSoCs" accepted for publication in ACM Transactions on Embedded Computing Systems, Special Issue on ACM/IEEE International Conference on Hardware/Software Codesign and System Synthesis, October 2017. Data Supporting Figures: Figure 1 - Execution time (ET) and energy consumption (EC) at varying fraction of application workload (threads) to be executed on CPU cores. Figure 2 - Execution time (ET) and total energy consumption (EC) for executing (a) individual and (b) concurrent applications (Mix) without (w/o) and with (w/) repartitioning. Figure 5 - Profiling results on CPU and GPU cores. Figure 6 - Design points representing performance and energy consumption for SYR2K application. Figure 7 - Energy consumption by employing various approaches for different application scenarios representing (a) 2 concurrent applications, (b) 3 concurrent applications and (c) single application. Figure 8 - Performance deviation from the requirement. Figure 9 - Run-time overhead of the proposed approach. Figure 10 - Energy consumption at varying performance constraints. Figure 11 - Energy consumption for real-world application mixes.