Rollback-Free Value Prediction with Approximate Loads
This paper presents a novel approach to Value Prediction by implementing Rollback-Free techniques with Approximate Loads. The research, conducted by Bradley Thwaites, Gennady Pekhimenko, Amir Yazdanbakhsh, Jongse Park, Girish Mururu, Hadi Esmaeilzadeh, Onur Mutlu, and Todd Mowry from Georgia Institute of Technology and Carnegie Mellon University, showcases the potential impact of this method in improving performance and efficiency in computer systems.
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Presentation Transcript
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
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
Design Principles Maximize opportunities for performance and energy benefits Minimize the adverse effects of approximation on quality degradation
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
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
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
