Topology-Aware Parallelism for NUMA Copying Collectors

Abstract. NUMA-aware parallel algorithms in runtime systems attempt to improve locality by allocating memory from local NUMA nodes. Re-searchers have suggested that the garbage collector should profile mem-ory access patterns or use object locality heuristics to determine the tar-get NUMA node before moving an object. However, these solutions are costly when applied to every live object in the reference graph. Our earlier research suggests that connected objects represented by the rooted sub-graphs provide abundant locality and they are appropriate for NUMA architecture. In this paper, we utilize the intrinsic locality of rooted sub-graphs to improve parallel copying collector performance. Our new topology-aware parallel copying collector preserves rooted sub-graph integrity by moving the connected objects as a unit to the target NUMA node. In addition, it distributes and assigns the copying tasks to appropriate (i.e. NUMA node local) GC threads. For load balancing, our solution enforces locality on the work-stealing mechanism by stealing from local NUMA nodes only. We evaluated our approach on SPECjbb2013, DaCapo 9.12 and Neo4j. Results show an improvement in GC performance by up to 2.5x speedup and 37 % better application performance

Bosschere. Object-relative addressing: Compressed pointers in 64-bit java virtual machines

Abstract. 64-bit address spaces come at the price of pointers requiring twice as much memory as 32-bit address spaces, resulting in increased memory usage. This paper reduces the memory usage of 64-bit pointers in the context of Java virtual machines through pointer compression, called Object-Relative Addressing (ORA). The idea is to compress 64-bit raw pointers into 32-bit offsets relative to the referencing object’s virtual address. Unlike previous work on the subject using a constant base address for compressed pointers, ORA allows for applying pointer compression to Java programs that allocate more than 4GB of memory. Our experimental results using Jikes RVM and the SPECjbb and DaCapo benchmarks on an IBM POWER4 machine show that the overhead introduced by ORA is statistically insignificant on average compared to raw 64-bit pointer representation, while reducing the total memory usage by 10 % on average and up to 14.5 % for some applications.

SPREE: Object Prefetching for Mobile computers

Mobile platforms combined with large databases promise new opportunities for mobile applications. However, mobile computing devices may experience frequent communication loss while in the field