The invention relates to a GRAPES system optimization method based on a parallel supercomputing grid cloud platform. The method comprises the steps that (S1) a test dataset is loaded, a system is run,and (S1.1) a system-level test, (S1.2) a communication-level test and (S1.3) a function-level test are performed separately, wherein in the (S1.3) function-level test, a called function is monitored,and running features of the function are acquired; (S2), test result analysis is performed according to an exported system feature file, wherein test result analysis comprises (S2.1) system test result analysis, (S2.2) MPI communication-level test result analysis and (S2.3) function-level test result analysis; and (S3) optimization processing is performed according to analysis results, wherein optimization processing comprises vectorization, load balancing and replacement of a function in a GRAPES_GFS by use of a library function. Through the method, optimization of Grapes on the parallel supercomputing grid platform is realized, and system running efficiency is improved.