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MICRO2025顶会

LoopFrog: In-Core Hint-Based Loop Parallelization

Márton Erdos, Utpal Bora, Akshay Bhosale, Bob Lytton, Ali Mustafa Zaidi, Alexandra W. Chadwick, Yuxin Guo, Giacomo Gabrielli, Timothy M. Jones

2025年份
1被引次数

摘要

To scale ILP, designers build deeper and wider out-of-order superscalar CPUs.However, this approach incurs quadratic scaling complexity, area, and energy costs with each generation.While small loops may benefit from increased instruction-window sizes and large loops may see speedups via thread-level parallelism across cores, there remains unexploited medium-granularity parallelism.We propose LoopFrog to tap into this potential by bringing thread-level speculation schemes into the modern era.LoopFrog runs multiple loop iterations from a single thread in parallel within the microarchitecture.The core can spawn future loop iterations as new microarchitectural threadlets based on compiler-inserted hints, which can leapfrog execution beyond the parent thread's instruction window, exposing a new, medium-grained parallelism, orthogonal to traditional ILP and TLP.LoopFrog monitors data dependencies between executing threadlets, forwards data for true dependencies and squashes speculative threadlets on ordering violations.Using an LLVM-based compiler to insert hints, we achieve a geometric mean loop speedup of 43%, translating to whole-program speedups of 9.2% on SPEC CPU 2006 and 9.5% on SPEC CPU 2017 benchmarks, with only modest area and power overheads.

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