Confluence: Unified Instruction Supply for Scale-out Servers

Cansu Kaynak, Boris Grot, Babak Falsafi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Multi-megabyte instruction working sets of server workloads defy the capacities of latency-critical instruction-supply components of a core; the instruction cache (L1-I) and the branch target buffer (BTB). Recent work has proposed dedicated prefetching techniques aimed separately at L1-I and BTB, resulting in high metadata costs and/or only modest performance improvements due to the complex control-flow histories required to effectively fill the two components ahead of the core's fetch stream.

This work makes the observation that the metadata for both the L1-I and BTB prefetchers require essentially identical information; the control-flow history. While the L1-I prefetcher necessitates the history at block granularity, the BTB requires knowledge of individual branches inside each block. To eliminate redundant metadata and multiple prefetchers, we introduce Confluence -- a frontend design with unified metadata for prefetching into both L1-I and BTB, whose contents are synchronized. Confluence leverages a stream-based prefetcher to proactively fill both components ahead of the core's fetch stream. The prefetcher maintains the control-flow history at block granularity and for each instruction block brought into the L1-I, eagerly inserts the set of branch targets contained in the block into the BTB. Confluence provides 85% of the performance improvement provided by an ideal frontend (with a perfect L1-I and BTB) with 1% area overhead per core, while the highest-performance alternative delivers only 62% of the ideal performance improvement with a per-core area overhead of 8%.
Original languageEnglish
Title of host publicationMICRO-48 Proceedings of the 48th International Symposium on Microarchitecture
Place of PublicationNew York, NY, USA
Number of pages12
ISBN (Print)978-1-4503-4034-2
Publication statusPublished - 2015

Keywords / Materials (for Non-textual outputs)

  • branch prediction, instruction streaming


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