SmartSweep: Efficient Space Reclamation in Tiered Managed Heaps

Using remote memory for the Java heap enables big data analytics frameworks to process large datasets. However, the Java Virtual Machine (JVM) runtime struggles to maintain low network traffic during garbage collection (GC) and to reclaim space efficiently. To reduce GC cost in big data analytics, systems group long-lived objects into regions and excludes them from frequent GC scans, regardless of whether the heap resides in local or remote memory. Recent work uses a dual-heap design, placing short-lived objects in a local heap and long-lived objects in a remote region-based heap, limiting GC activity to the local heap. However, these systems avoid scanning by reclaiming remote heap space only when regions are fully garbage, an inefficient strategy that delays reclamation and risks out-of-memory (OOM) errors.