The heterogeneous wireless network is an essential constituent of the emerging advanced active media technology (AMT). However, reliable wireless data communication is a challenge since a packet is easily corrupted by noise or interference. As a remedy, error control mechanisms are adopted and ever-growing networks demand a high speed solution. In this paper, we present a faster implementation of the extended Hamming code, a widely-used error correction algorithm, using graphics processing units (GPU). A GPU performs parallel computations by employing a cluster of processors, and can operate on both single bit and multiple bit errors. We compare the performance of the GPU-based approach with the equivalent sequential algorithm that runs on traditional CPUs with regards to error strength, t, such that 1≤t≤7. Experimental results demonstrate that the GPU-based approach significantly outperforms the CPU-based approach in terms of execution time and buffer memory requirement. Furthermore, the proposed approach reduces the computational complexity from O(n) for CPUs to O(1) for the GPU-based approach, yielding significant increases in speed.