Long Term Parking (LTP): Criticality-aware Resource Allocation in OOO Processors

Abstract : Modern processors employ large structures (IQ, LSQ, register file, etc.) to expose instruction-level parallelism (ILP) and memory-level parallelism (MLP). These resources are typically allocated to instructions in program order. This wastes resources by allocating resources to instructions that are not yet ready to be executed and by eagerly allocating resources to instructions that are not part of the application's critical path. This work explores the possibility of allocating pipeline resources only when needed to expose MLP, and thereby enabling a processor design with significantly smaller structures, without sacrificing performance. First we identify the classes of instructions that should not reserve resources in program order and evaluate the potential performance gains we could achieve by delaying their allocations. We then use this information to " park " such instructions in a simpler, and therefore more efficient , Long Term Parking (LTP) structure. The LTP stores instructions until they are ready to execute, without allocating pipeline resources, and thereby keeps the pipeline available for instructions that can generate further MLP. LTP can accurately and rapidly identify which instructions to park, park them before they execute, wake them when needed to preserve performance, and do so using a simple queue instead of a complex IQ. We show that even a very simple queue-based LTP design allows us to significantly reduce IQ (64 → 32) and register file (128 → 96) sizes while retaining MLP performance and improving energy efficiency.
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https://hal.inria.fr/hal-01225019
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Submitted on : Thursday, November 5, 2015 - 2:53:21 PM
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Andreas Sembrant, Trevor Carlson, Erik Hagersten, David Black-Shaffer, Arthur Perais, et al.. Long Term Parking (LTP): Criticality-aware Resource Allocation in OOO Processors. International Symposium on Microarchitecture, Micro 2015, Dec 2015, Honolulu, United States. pp.11. ⟨hal-01225019⟩

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