Cache performance of garbage-collected programs
PLDI '94 Proceedings of the ACM SIGPLAN 1994 conference on Programming language design and implementation
Optimistic stack allocation for java-like languages
Proceedings of the 5th international symposium on Memory management
Memory management for self-adjusting computation
Proceedings of the 7th international symposium on Memory management
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Heap allocation with copying garbage collection is a general storage management technique for modern programming languages. It is believed to have poor memory subsystem performance. To investigate this, we conducted an in-depth study of the memory subsystem performance of heap allocation for memory subsystems found on many machines. We studied the performance of mostly-functional Standard ML programs which made heavy use of heap allocation. We found that most machines support heap allocation poorly. However, with the appropriate memory subsystem organization, heap allocation can have good performance. The memory subsystem property crucial for achieving good performance was the ability to allocate and initialize a new object into the cache without a penalty. This can be achieved by having subblock placement with a subblock size of one word with a write allocate policy, along with fast page-mode writes or a write buffer. For caches with subblock placement, the data cache overhead was under 9% for a 64K of larger data cache; without subblock placement the overhead was often higher than 50%.