Bounded incoherence

Ren, Yuxin; Parmer, Gabriel

doi:10.1145/3380536.3380541

Cited by 2 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, Treadmarks 28 integrates consistency with lock semantics, and distributed shared memory implementations manually overlays consistency over a network 29‐31 . Some research 21,22,32 explicitly relax data consistency and introduce data staleness in distributed systems. Bounded staleness 21 is exploited to accelerate big data analytics, where the algorithm can see old data from previous iterations.…”

Section: Related Workmentioning

confidence: 99%

Sharing non‐cache‐coherent memory with bounded incoherence

Ren

Parmer

Milojičić

2021

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

Summary Cache coherence in modern computer architectures enables easier programming by sharing data across multiple processors. Unfortunately, it can also limit scalability due to cache coherency traffic initiated by competing memory accesses. Rack‐scale systems introduce shared memory across a whole rack, but without inter‐node cache coherence. This poses memory management and concurrency control challenges for applications that must explicitly manage cache‐lines. To fully utilize rack‐scale systems for low‐latency and scalable computation, applications need to maintain cached memory accesses in spite of non‐coherency. This paper introduces Bounded Incoherence, a memory consistency model that enables cached access to shared data‐structures in non‐cache‐coherency memory. It ensures that updates to memory on one node are visible within at most a bounded amount of time on all other nodes. We evaluate this memory model on modified PowerGraph graph processing framework, and boost its performance by 30% with eight sockets by enabling cached‐access to data‐structures.

show abstract

Section: Related Workmentioning

confidence: 99%