Hybrid platforms combining multicore central processing units (CPU) with manycore hardware accelerators such as graphic processing units (GPU) can be smartly exploited to provide efcient parallel implementations of wireless communication algorithms for Fifth Generation (5G) and beyond systems. Massive multiple-input multiple-output (MIMO) systems are a key element of the 5G standard, involving several tens or hundreds of antenna elements for communication. Such a high number of antennas has a direct impact on the computational complexity of some MIMO signal processing algorithms. In this work, we focus on the channel estimation stage. In particular, we develop a parallel implementation of a recently proposed MIMO channel estimation algorithm. Its performance in terms of execution time is evaluated both in a multicore CPU and in a GPU. The results show that some computation blocks of the algorithm are more suitable for multicore implementation, whereas other parts are more efciently implemented in the GPU, indicating that a hybrid CPU-GPU implementation would achieve the best performance in practical applications based on the tested platform.