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Systems integrating heterogeneous processors with unified memory provideseamless integration among these processors with minimal developmentcomplexity. These systems integrate accelerators such as GPUs on the same diewith CPU cores to accommodate running parallel applications with varying levelsof parallelism. Such integration is becoming very common on modern chiparchitectures, and it places a burden (or opportunity) on application andsystem programmers to utilize the full potential of such integrated chips. Inthis paper we evaluate whether we can obtain any performance benefits fromrunning garbage collection on integrated GPU systems, and discuss how difficultit would be to realize these gains for the programmer.  Proliferation of garbage-collected languages running on a variety ofplatforms from handheld mobile devices to data centers makes garbage collectionan interesting target to examine on such platforms and can offer valuablelessons for other applications. We present our analysis of running garbagecollection on integrated systems and find that the current state of thesesystems does not provide an advantage for accelerating such a task. We build aframework that allows us to offload garbage collection tasks on integrated GPUsystems from within the JVM. We identify dominant phases of garbage collectionand study the viability of offloading them to the integrated GPU. We show thatperformance advantages are limited, partly because an integrated GPU haslimited advantage in memory bandwidth over the CPU, and partly because ofcostly atomic operations.

Trash Talk: Accelerating Garbage Collection on Integrated GPUs is Worthless