An objective in the field of EM-based wave decomposition when dealing with full-wave Li DAR data is to improve the processing efficiency. We proposed a method that parallels the EM algorithm on GPGPU.（ 1） Considering CUDA memory hierarchy that can access shared memory and texture memory with high speed

we designed an overall parallel framework.（ 2） A median can be obtained from the histogram of the waveform sampling values that are stored in bytes to reduce the complexity of noise threshold calculation.（ 3） A parallel strategy for summation was applied to improve the accumulation efficiency during the EM iterative process. Results indicated that the GPU speed ratio using the proposed method can reach 8 when meet the following conditions:（ 1） Proper parallel parameter setting;（ 2） EM iteration number is larger than 16;（ 3） Data size is larger than 64 MB.Therefore

the processing efficiency of full-wave decomposition can be significantly improved under the GPU parallel computing framework.