This study focuses on a new planning method for fixture conditions of workpiece in the continuous multi-axis controlled machining process. Generally, the motion of translational axes on machine tools with a trunnion table is significantly effected by the machine tool structure, tool posture in CL data, and position/posture of the workpiece on the trunnion table. In some cases, rapid changes in the tool posture at cutter locations away from the center of the rotational axis, significantly shifts the translational axes. However, in conventional CAM schemes, tool posture changes in CL data are determined without considering the machine tool structure and fixture conditions. And, a planning method for determining the fixture conditions, which prevent the rapid motion of translational axes and reduce the energy consumption for planned CL data by CAM systems, has not yet been proposed.In this paper, we therefore propose a new planning method for determining the workpiece position and posture on the trunnion table of a multi-axis-controlled machine tool. The proposed method consists of two different steps. In the first step, a large number of potential fixture conditions are assumed automatically. Second, the distribution of features about the movement on translation axes is estimated by coordinate transformation and collision detection. To deal with a large number of potential fixture conditions and significantly reduce the computation time for repetition of post processing, an ultra parallel computing technology known as GPGPU is introduced into the planning algorithms. The developed system can estimate the total energy consumption on the translational axes and the total machining time for each potential workpiece fixture. Therefore, the developed system can assist an NC operator to select optimum fixture conditions in a short time.