Performance Adjustment of an APL Interpreter

An APL interpreter is analyzed to examine how microprogramming can improve its performance. Also examined is how the modularization method or program structure affects performance improvement. Two basic modularization methods, function and data modularizations, are investigated. We rind that the performance gain may reach 100-time speed-up and that a proper selection of modules is very important to obtain the maximum performance gain under a limited microprogram memory. We also find that both the function and the data modularizations provide the same degree of performance improvement despite the finding that they tend to affect the complementary parts of a program.