Enhancing Processor Performance Through Rollback-Free Value Prediction

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Mitigating memory and bandwidth walls, this research extends rollback-free value prediction to GPUs, achieving up to 2x improvement in energy and performance while maintaining 10% quality degradation. Utilizing microarchitecturally-triggered approximation to predict missed loads, this work focuses on maximizing performance benefits while minimizing approximation's impact on quality. Experimental results on a modern Out-of-Order processor demonstrate the effectiveness of the approach. Ongoing work explores further extensions to GPUs and dropping fractions of missed requests to enhance system performance.


Uploaded on Sep 25, 2024 | 0 Views


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  1. Rollback-Free Value Prediction with Approximate Loads Bradley Thwaites Gennady Pekhimenko Amir Yazdanbakhsh JongsePark Girish Mururu Hadi Esmaeilzadeh Onur Mutlu Todd Mowry Georgia Institute of Technology Carnegie Mellon University

  2. Mitigating Memory Wall with Approximation Rollback-Free Value Prediction Microarchitecturally-triggered approximation Predict the value of an approximate load when it misses in the cache Do not check for mispredictions Do not rollback from mispredictions Mitigate long latency memory accesses

  3. Rollback Free Value Prediction

  4. Design Principles Maximize opportunities for performance and energy benefits Minimize the adverse effects of approximation on quality degradation

  5. Design Challenges and Solutions Target Performance-Critical Safe Loads Profile-directed compilation Usually, < 32 loads cause 80% of cache misses Utilize Fast-Learning Predictors Two-delta stride predictor Prediction: table lookup plus an addition Integrate RFVP with existing architecture

  6. Experimental Results with a Modern OoO Processor 2MB LLC, 4-Wide, Performance Results Two-Delta Value Prediction - Quality Loss 1.25 100% 90% 1.20 80% Performance Benefit 70% Quality Loss 1.15 60% 50% 1.10 40% 30% 1.05 20% 10% 1.00 0% 0.8% Average 1.8% Maximum 8% Average 19% Maximum More CPU configurations and value predictors are in the paper

  7. Ongoing Work Mitigate both Memory Wall and Bandwidth Wall Extend rollback-free value prediction to GPUs Drop a fraction of the missed requests Preliminary results: Up to 2x improvement in energy and performance with only 10% quality degradation

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