Energy consumption in computing presents significant environmental concerns, and reducing it has become a major technological challenge. The accurate measurement of energy consumption during application execution is essential for implementing effective application-level energy minimization techniques. The two widely-used methods for measuring energy consumption are system-level physical measurements using external power meters and software-based power measurement tools. In this work, we present an experimental comparative analysis that evaluates the accuracy of hardware and various software-based power measurement tools in measuring application energy consumption of CPU based data-parallel workloads. Our analysis focused on compute-intensive kernels operating across multiple processing units, where accurate energy measurement is critical for performance tuning and energy efficiency. We extend this empirical study to highlight the strengths and limitations of each software-based power measurement tool. The results offer valuable insights on the accuracy of energy measurement tools for data-parallel workloads, particularly when relying on software tools.