Lune

OSDI2021Top-tier venue

Optimizing Storage Performance with Calibrated Interrupts

Amy Tai, Igor Smolyar, Michael Wei, Dan Tsafrir

2021Year
7Top-tier citations

Abstract

After request completion, an I/O device must decide whether to minimize latency by immediately firing an interrupt or to optimize for throughput by delaying the interrupt, anticipating that more requests will complete soon and help amortize the interrupt cost. Devices employ adaptive interrupt coalescing heuristics that try to balance between these opposing goals. Unfortunately, because devices lack the semantic information about which I/O requests are latency-sensitive, these heuristics can sometimes lead to disastrous results.

Instead, we propose addressing the root cause of the heuristics problem by allowing software to explicitly specify to the device if submitted requests are latency-sensitive. The device then "calibrates" its interrupts to completions of latency-sensitive requests. We focus on NVMe storage devices and show that it is natural to express these semantics in the kernel and the application and only requires a modest two-bit change to the device interface. Calibrated interrupts increase throughput by up to 35%, reduce CPU consumption by as much as 30%, and achieve up to 37% lower latency when interrupts are coalesced.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 06e432cb-d46b-45a2-bad7-43034d7a161e

Cited by top-tier papers7

Ask how each one uses it

Builds on3

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines