Abstract: This paper proposes a massively parallel FIR filter algorithm with its GPU implementation to improve the efficiency and scalability of GPU based FIR.By the algorithm proposed,the problem is formulated as a matrix multiplication operation that offers sufficient data level parallelism for parallel filtering on modern GPUs.In addition,the GPU implementation guarantees that each thread could complete a two-signal operation within a single instruction cycle.Efficient and effective strategies for load balancing and memory mapping are also introduced to further improve the performance.The proposed algorithm and the corresponding GPU implementation could achieve an efficient multi-channel signal filtering.Experimental results on a GTX260+ graphics card prove that the FIR filter algorithm could be used to deliver on average a speed-up of 203X and an efficiency increase over 40%.