This paper presents a parallel model termed as towerlike master-slave model (TMSM) for artificial immune systems.Based on TMSM

the parallel immune memory clonal selection algorithm (PIMCSA) is also designed for dealing with large-scale TSP problems.TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory.In PIMCSA

vaccines are extracted and migrated between populations rather than antibodies as has been done in parallel genetic algorithms

it is a good balance between the diversity maintenance of populations and the convergent speed of the algorithm.PIMCSA shows superiority over other compared approaches both in solution quality and computation time

and the lager the problem size the more outstanding the predominance will be.TMSM is a good simulation of biological immune system

and PIMCSA is a parallel artificial immune algorithm with good extensibility

which is capable of solving large scale and complex optimization problems.