Diverge-Merge Processor (DMP): Dynamic Predicated Execution of Complex Control-Flow Graphs Based on Frequently Executed Paths

  • Authors:

  • Hyesoon Kim;Jose A. Joao;Onur Mutlu;Yale N. Patt

  • Affiliations:

  • University of Texas at Austin;University of Texas at Austin;Microsoft Research;University of Texas at Austin

  • Venue:
  • Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
  • Year:
  • 2006

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Abstract

This paper proposes a new processor architecture for handling hard-to-predict branches, the diverge-merge processor (DMP). The goal of this paradigm is to eliminate branch mispredictions due to hard-to-predict dynamic branches by dynamically predicating them without requiring ISA support for predicate registers and predicated instructions. To achieve this without incurring large hardware cost and complexity, the compiler provides control-flow information by hints and the processor dynamically predicates instructions only on frequently executed program paths. The key insight behind DMP is that most control-flow graphs look and behave like simple hammock (if-else) structures when only frequently executed paths in the graphs are considered. Therefore, DMP can dynamically predicate a much larger set of branches than simple hammock branches. This paper proposes a new processor architecture for handling hard-to-predict branches, the diverge-merge processor (DMP). The goal of this paradigm is to eliminate branch mispredictions due to hard-to-predict dynamic branches by dynamically predicating them without requiring ISA support for predicate registers and predicated instructions. To achieve this without incurring large hardware cost and complexity, the compiler provides control-flow information by hints and the processor dynamically predicates instructions only on frequently executed program paths. The key insight behind DMP is that most control-flow graphs look and behave like simple hammock (if-else) structures when only frequently executed paths in the graphs are considered. Therefore, DMP can dynamically predicate a much larger set of branches than simple hammock branches.