Trash Talk: Accelerating Garbage Collection on Integrated GPUs is Worthless
Mohammad Dashti, Alexandra Fedorova

TL;DR
This paper evaluates the potential of using integrated GPUs to accelerate garbage collection in heterogeneous systems, finding limited performance gains due to hardware and operational constraints.
Contribution
The paper provides an analysis of garbage collection on integrated GPU systems and introduces a framework for offloading GC tasks from JVMs to GPUs.
Findings
Limited performance benefits from GPU offloading of garbage collection.
Memory bandwidth constraints reduce GPU advantages.
Atomic operation costs hinder GPU acceleration of GC.
Abstract
Systems integrating heterogeneous processors with unified memory provide seamless integration among these processors with minimal development complexity. These systems integrate accelerators such as GPUs on the same die with CPU cores to accommodate running parallel applications with varying levels of parallelism. Such integration is becoming very common on modern chip architectures, and it places a burden (or opportunity) on application and system programmers to utilize the full potential of such integrated chips. In this paper we evaluate whether we can obtain any performance benefits from running garbage collection on integrated GPU systems, and discuss how difficult it would be to realize these gains for the programmer. Proliferation of garbage-collected languages running on a variety of platforms from handheld mobile devices to data centers makes garbage collection an interesting…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Distributed systems and fault tolerance · Caching and Content Delivery
