The design and evaluation of a high performance SMALLTALK system
The design and evaluation of a high performance SMALLTALK system
Simple generational garbage collection and fast allocation
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We describe a method of measuring lifetime characteristics of heap objects, and discuss ways in which such quantitative object behaviour measurements can help improve language implementations, especially garbage collection performance. For Standard ML of New Jersey, we find that certain primary aspects of object behaviour are qualitatively the same across benchmark programs, in particular the rapid object decay. We show that the heap-only allocation implementation model is the cause of this similarity. We confirm the weak generational hypothesis for SML/NJ and discuss garbage collector configuration tuning. Our approach is to obtain object statistics directly from program execution, rather than simulation, for reasons of simplicity and speed. Towards this end, we exploit the flexibility of the garbage collector toolkit as a measurement tool. Careful numerical analysis of the acquired data is necessary to arrive at relevant object lifetime measures. This study fills a gap in quantitative knowledge of the workings of heap-based compilers and their run-time systems, and should be useful to functional language implementors.