Four-dimensional Lattice Spring Model (4D-LSM) is a newly developed discrete numerical method considering the extra-dimensional interaction. The method needs large amounts of computing resources in three-dimensional rock failure analysis and therefore is not suitable for the conventional personal computer (PC). In this work, based on the multi-core parallel technology, the computational performance and bottleneck of 4D-LSM were analyzed in details. A variety of hardware environments, such as Alibaba cloud, multi-core PC, and multi-core workstation, were selected to investigate effects of the model size, problem type, thread number and hardware configuration on the parallel computing performance. It is found that the memory capacity determines the limit size of the computable model, and the computational time of the elastic problem is proportional to the model size. The parallel computing efficiency is affected by both the CPU performance and memory bandwidth. The flexibility of cloud computing in multi-core matching and memory allocation is especially suitable for parallel computing of 4D-LSM without considering the economic factor. Through analysis, it is found that the maximum size of 4D-LSM based on Alibaba cloud can reach 1 billion particles. However, due to the bottleneck lies on the pre-processing and post-processing, the current maximum capacity of 4D-LSM is still limited to 20 million particles. Finally, as an example, 4D-LSM was used to solve a three-dimensional coin-shaped crack propagation problem.