Efficient nursery sizing for managed languages on multi-core processors with shared caches

Abstract

In modern programming languages, automatic memory management has become a standard feature for allocating and freeing memory. In this paper, we show that the performance of today’s managed languages can degrade significantly due to cache contention among multiple concurrent applications that share a cache. To address this problem, we propose to change the programs’ memory access patterns by adjusting the nursery size. We propose Dynamic Nursery Allocator (DNA), an online dynamic scheme that automatically adjusts the nursery sizes of multiple managed-language programs running concurrently without any prior knowledge or offline profiling. The experimental results on a native Intel machine show that DNA can significantly improve the system throughput by 16.3% on average and as much as 73% over today’s nursery sizing scheme when four applications run concurrently sharing the last-level cache.