Quantifying the performance of garbage collection vs. explicit memory management

Matthew Hertz, Emery D. Berger
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Read: 18 April 2021

Proceedings of the 20th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications
San Diego, CA, USA
Association for Computing Machinery
New York, NY, USA
Pages 313-326
Note(s): memory management, garbage collection

This paper uses CPU performance simulators and oracles to measure the impact of replacing Java’s garbage collectors with explicit memory management. They conclude that you need around 5x more physical memory before GC performs better than explicit memory management, it is 17% worse at a mere 3x and 70% worse at 2x memory.

Their basic setup is to

  1. measure object lifetimes in a heavily instrumented initial run
  2. determine the earliest and latest times that each object could possibly be deallocated by finding the last time the object is accessed and the time when the object first becomes unreachable
  3. perform two measurement runs where a conventional malloc/free-style memory allocator is used to deallocate objects at either the earliest or the latest possible time

The measurement runs are repeated with a variety of state of the art conventional memory allocators and compared against performance with a variety of garbage collectors that use mark-sweep, copying, generational and hybrid approaches.

They avoid interference from the cost of their oracles by running this all in a modified version of the SimpleScalar CPU simulator which allows them to remove oracle time. (But do they do anything to model the actual costs that an explicit memory allocation scheme needs to use to decide when to deallocate (reference counts, etc.)?)

Some of the costs that they are concerned with are impact on L1-D$, L2$, L3$ and virtual memory paging. In particular, they emphasize

  • the benefits of reusing recently allocated objects on cache miss rates (though later it seems this is not as conclusive as expected) when using explicit memory allocation
  • the disadvantages of periodically evicting recent objects from the memory cache
  • the significant cost of visiting virtual memory pages during garbage collection that are outside the working set of the application itself

They observe that

  • the cost of explicit memory management does not depend on heap size and is linear in the number of objects allocated
  • (as expected) the GC runtime is inversely proportional to the reachable heap size for non-generational collectors
  • (new observation) the GC runtime is inversely proportional to the heap size for generational collectors

They suggest future work of looking at region based allocators, BiBoP allocators (to remove overhead of object headers) and of comparing pauses in explicit memory allocators (when per-size quicklists are refilled) with the pauses in various GCs and of concurrent GCs.

Overall conclusion: if you are running in a memory constrained environment (can’t allocate 5x more memory than needed) or are running on a shared machine with other processes competing for physical memory, think twice about GC-based languages.