Ultrasound tomography is an emerging modality for breast imaging. However, most current ultrasonic tomography imaging algorithms, historically hindered by the limited memory and processor speed of computers, are based on ray theory and assume a homogeneous background which is inaccurate for complex heterogeneous regions. Therefore, wave theory, which accounts for diffraction effects, must be used in ultrasonic imaging algorithms to properly handle the heterogeneous nature of breast tissue in order to accurately image small lesions. However, application of waveform tomography to medical imaging has been limited by extreme computational cost and convergence. By taking advantage of the computational architecture of Graphic Processing Units (GPUs), the intensive processing burden of waveform tomography can be greatly alleviated. In this study, using breast imaging methods, we implement a frequency domain waveform tomography algorithm on GPUs with the goal of producing high-accuracy and high-resolution breast images on clinically relevant time scales. We present some simulation results and assess the resolution and accuracy of our waveform tomography algorithms based on the simulation data.