Allocation Folding Based on Dominance

Memory management system performance is of increasing impor-tance in today’s managed languages. Two lingering sources of over-head are the direct costs of memory allocations and write barriers. This paper introduces allocation folding, an optimization technique where the virtual machine automatically folds multiple memory al-location operations in optimized code together into a single, larger allocation group. An allocation group comprises multiple objects and requires just a single bounds check in a bump-pointer style allo-cation, rather than a check for each individual object. More impor-tantly, all objects allocated in a single allocation group are guaran-teed to be contiguous after allocation and thus exist in the same gen-eration, which makes it possible to statically remove write barriers for reference stores involving objects in the same allocation group. Unlike object inlining, object fusing, and object colocation, alloca-tion folding requires no special connectivity or ownership relation between the objects in an allocation group. We present our analysis algorithm to determine when it is safe to fold allocations together and discuss our implementation in V8, an open-source, production JavaScript virtual machine. We present performance results for the Octane and Kraken benchmark suites and show that allocation fold-ing is a strong performance improvement, even in the presence of some heap fragmentation. Additionally, we use four hand-selected benchmarks JPEGEncoder, NBody, Soft3D, and Textwriter where allocation folding has a large impact