Python多处理比单个处理花费更长的时间

I am performing some large computations on 3 different numpy 2D arrays sequentially. The arrays are huge, 25000x25000 each. Each computation takes significant time so I decided to run 3 of them in parallel on 3 CPU cores on the server. I am following standard multiprocessing guideline and creating 2 processes and a worker function. Two computations are running through the 2 processes and the third one is running locally without separate process. I am passing the huge arrays as arguments of the processes like :I am performing some large computations on 3 di