Parallel memory defragmentation on a GPU

High-throughput memory management techniques such as malloc/free or mark-and-sweep collectors often exhibit memory fragmentation leaving allocated objects interspersed with free memory holes. Memory defragmentation removes such holes by moving objects around in memory so that they become adjacent (compaction) and holes can be merged (coalesced) to form larger holes. However, known defragmentation techniques are slow. This paper presents a parallel solution to best-effort partial defragmentation that makes use of all available cores. The solution not only speeds up defragmentation times significantly, but it also scales for many simple cores. It can therefore even be implemented on a GPU.