JILP RESULTS 1

JILP Experimental Framework Goal Simplicity of a trace based simulator Flexibility to model special predictors ( e.g., using data values) Trace driven with pipeline timing information Tracing Methodology: Detailed timing simulator with perfect branch predictor 50M uops per trace Traces include pipeline behavior/timing, instruction address, uop type etc. 2

JILP Experiments Workloads 40 workloads selected from a large pool of applications 5 classes: CLIENT 16, INT 6, MM 7, SERVER 5, WS 6 Metrics Arithmetic average of MPPKI ( Misprediction Penalty per Kilo Instructions) 3 No secret workloads

JILP Conditional predictor results #1 A. Seznec, A 64 Kbytes ISL-TAGE branch predictor, MPPKI 568 #2 Y. Ishii, K. Kuroyanagi, T. Sawada, M. Inaba, K. Hiraki, Revisiting Local History for Improving Fused Two-Level Branch Predictor, MPPKI 581 #3 D. Jimenez, OH-SNAP: Optimized Hybrid Scaled Neural Analog Predictor, MPPKI 598 #4 Y. Hu, D. Koppelman and L. Peng, Penalty-Sensitive L-TAGE Predictor, MPPKI 608 #5 G. Shi and M. Lipasti, Perceptron Branch Prediction with Separated Taken/Not-Taken Weight Tables, MPPKI 677 4

JILP Indirect predictor results #1 A. Seznec, A 64-Kbytes ITTAGE indirect branch predictor, MPPKI 34.1 #2 Y. Ishii, T. Sawada, K. Kuroyanagi, M. Inaba, K. Hiraki, Bimode Cascading: Adaptive Rehashing for ITTAGE Indirect Branch Predictor, MPPKI 37.0 #3 N. Bhansali, C. Panirwala, H. Zhou, Exploring Correlation for Indirect Branch Prediction, MPPKI 51.6 #4 Daniel A. Jimenez, SNIP: Scaled Neural Indirect Predictor, MPPKI

JILP Discussions From industry perspective It is important! Perf gain from better branch predictors Branch prediction papers Total perf gain from uarch changes uarch papers What do we need from researchers? What’s next? 6

JILP Detailed Results 7 Conditional Track 01_shi02_jimenez03_seznec04_hu05_ishii CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT INT INT INT INT INT INT MM MM MM MM MM MM MM SERVER SERVER SERVER SERVER SERVER WS WS WS WS WS WS AVG Indirect Track 06_bhansali07_seznec08_ishii09_jimenez CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT CLIENT INT INT INT INT INT INT MM MM MM MM MM MM MM SERVER SERVER SERVER SERVER SERVER WS WS WS WS WS WS AVG