We developed a highly parallel simulator of Optical Coherence Tomography (OCT) of objects with arbitrary spatial distributions. This Monte Carlo method based simulator models the object as a tetrahedron-based mesh, and implements an advanced importance sampling scheme. This new method makes OCT simulations more practical, since the corresponding serial Central Processing Unit (CPU) based implementation requires approximately 360 hours to simulate OCT imaging of a single B-scan. We implemented this new simulator on Graphics Processing Units (GPUs) using the Compute Unified Device Architecture (CUDA) platform and programming model by NVIDIA. We demonstrated that our new simulator requires one order of magnitude less time, compared to its serial implementation, to simulate the same OCT images. Our new parallel OCT simulator could be an important and practical tool to study different OCT phenomena and to design novel OCT systems with superior imaging performance.