GPUs as an Opportunity for Offloading Garbage Collection
University of California, Berkeley
2012 international symposium on Memory Management (ISMM ’12), 2012
@inproceedings{maas2012gpus,
title={GPUs as an opportunity for offloading garbage collection},
author={Maas, M. and Reames, P. and Morlan, J. and Asanovi{‘c}, K. and Joseph, A.D. and Kubiatowicz, J.},
booktitle={Proceedings of the 2012 international symposium on Memory Management},
pages={25–36},
year={2012},
organization={ACM}
}
GPUs have become part of most commodity systems. Nonetheless, they are often underutilized when not executing graphics-intensive or special-purpose numerical computations, which are rare in consumer workloads. Emerging architectures, such as integrated CPU/GPU combinations, may create an opportunity to utilize these otherwise unused cycles for offloading traditional systems tasks. Garbage collection appears to be a particularly promising candidate for offloading, due to the popularity of managed languages on consumer devices. We investigate the challenges for offloading garbage collection to a GPU, by examining the performance trade-offs for the mark phase of a mark & sweep garbage collector. We present a theoretical analysis and an algorithm that demonstrates the feasibility of this approach. We also discuss a number of algorithmic design trade-offs required to leverage the strengths and capabilities of the GPU hardware. Our algorithm has been integrated into the Jikes RVM and we present promising performance results.
June 29, 2012 by hgpu
