In sharp contrast to conventional performance indicative based Network-on-Chip (NoC) DVFS, where the direct relation between application performance and NoC power consumption is missing, we exploit the concept of Performance-Power Characteristic Curve (PPCC) newly proposed in the literature to approach maximum NoC power efficiency. PPCC, which defines the direct relation between application performance and NoC power consumption, consists of three distinct regions: an inertial region due to power under-provisioning, a linear region for proportional performance gain, and a saturation region due to power over-provisioning. With PPCC as a guidance, we propose Δ-DVFS, which employs a “profile-then-select” strategy to step-by-step approach maximum NoC power efficiency. Δ-DVFS is built on two observations. First, in multi-threaded applications, maximum NoC power efficiency is achieved at the boundary between the linear region and the saturation region on the PPCC. Second, PPCC stabilizes when threads repeat workloads of the same loop. This is intuitively meaningful because loop repetition stresses NoC with similar workload. Based on the observations, Δ-DVFS uses the first several loop iterations for PPCC profiling. After the profiling is done, Δ-DVFS selects and applies the optimal V/F that achieves maximum NoC power efficiency to the remaining loop iterations. To accurately and timely follow PPCC when threads proceed to different loops, Δ-DVFS utilizes an H-tree loop monitor to detect loop change among distributive threads.