Improving program locality in the GC using hotness

Yang, Albert Mingkun; Österlund, Erik; Wrigstad, Tobias

doi:10.1145/3385412.3385977

Cited by 13 publications

(3 citation statements)

References 18 publications

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“…In contrast, our analysis extends to concurrent collectors and their impact on application locality and aims to show the effects of widely-used production GCs on application performance. Yang et al [31] also conduct an investigation focused on GC impact on application performance from a cache locality perspective. They evaluate ZGC in this context and propose a new heap organisation that improves application locality.…”

Section: Related Workmentioning

confidence: 99%

“…They evaluate ZGC in this context and propose a new heap organisation that improves application locality. However, the authors of [31] measure cache-level events for the whole JVM runs, instead of the application thread alone, warning that these results should be taken "with a grain of salt". Our extensive and targeted analysis complements this work with precise insights regarding the GC effect on application data locality in the caches.…”

Section: Related Workmentioning

confidence: 99%

“…They access and move objects in memory that do not necessarily belong to the effective working-set of the application, potentially polluting the cache. Therefore, concurrent collectors are commonly blamed in the literature for harming application locality [31].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Concurrent GCs and Modern Java Workloads: A Cache Perspective

Carpen-Amarie¹,

Vavouliotis²,

Tovletoglou³

et al. 2023

Proceedings of the 2023 ACM SIGPLAN International Symposium on Memory Management

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The garbage collector (GC) is a crucial component of language runtimes, offering correctness guarantees and high productivity in exchange for a run-time overhead. Concurrent collectors run alongside application threads (mutators) and share CPU resources. A likely point of contention between mutators and GC threads and, consequently, a potential overhead source is the shared last-level cache (LLC).This work builds on the hypothesis that the cache pollution caused by concurrent GCs hurts application performance. We validate this hypothesis with a cache-sensitive Java micro-benchmark. We find that concurrent GC activity may slow down the application by up to 3 × and increase the LLC misses by 3 orders of magnitude. However, when we extend our analysis to a suite of benchmarks representative for today's server workloads (Renaissance), we find that only 5 out of 23 benchmarks show a statistically significant correlation between GC-induced cache pollution and performance. Even for these, the performance overhead of GC does not exceed 10 %. Based on further analysis, we conclude that the lower impact of the GC on the performance of Renaissance benchmarks is due to their lack of sensitivity to LLC capacity. CCS Concepts:• Software and its engineering → Runtime environments; Garbage collection; • Computer systems organization → Multicore architectures.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%