Karl Taht's Research Paper Blog

Authors: Canturk Isci, Gilberto Contreras, and Margaret Martonosi Venue:   MICRO 2006 The authors of this paper present a real-system framework which enables phase detection, phase prediction, and system reconfiguration. The phase detection is done using performance counters, more specifically, phases are classified based on their ratio of memory bus transitions to micro-ops retired. This is mapped to how compute vs. memory bound an application is, and thus, the DVFS can be adjusted accordingly. Phase prediction is done in a similar fashion to the TAGE branch predictor, using a global history table which tracks 1024 entries and a history of 8. The framework achieves an 18% EDP improvement with a 4% performance loss on average across SPEC 2000 benchmarks. Note that their phase detection framework and performance counter selection is geared specifically toward DVFS optimization, and is justified through analysis in the paper which demonstrates a specific relationship present....

Authors: Xiaofei Liao, Rentong Guo, Danping Yu Venue:    International Journal of Parallel Programming 2016 The authors present a novel dynamic cache partitioning mechanism based on the phase behavior of program. They use a similar phase detection to Sembrant et al. to detect phases. To reduce the overhead further, they make an assumption that the current phase will continue, and trigger only a phase change when the IPC deviates more than a threshold. To partition the cache, they utilize their FractalMRC algorithm, which predicts the optimal cache partitioning via a miss-rate-curve. If the phase is already seen, then the MRC will be stored in the table. They show that overall their approach nets up to 21.4% performance improvement using Spec2006 benchmarks. The authors cite low overhead ~1%-2% on average in various configurations. However, it is unclear if this also factors in the overhead of the FractalMRC algorithm, which they state has an overhead of "less than 1s to c...

Authors: Andreas Sembrant, David Black-Schaffer, Erik Hagersten Venue:    IISWC 2012 This paper extends ScarPhase to be feasible in a multi-threaded environment. This is made possible by tracking the same data as ScarPhase on a per-phase basis. The authors make note that global sharing (phase IDs, phase predictors) does not improve performance much, this seems to be due to the fact that when new "phases" arrive, they arrive simultaneously in multiple threads. Thus global sharing would not improve the accuracy or quality of the phase detection, but rather remove redundancy. However, the redundancy may be preferable from an implementation perspective. This paper primary focus on workload analysis rather than the phase detection algorithm. The authors show that PARSEC displays much less phase behavior when compared to Spec2006. Additionally, as the number of threads scales in data-parallel applications, phases becoming increasingly shorter (assuming the same data), and eventuall...

Authors: Andreas Sembrant, David Eklov, Erik Hagersten Venue:    IISWC 2011 The authors develop an online phase detection algorithm that works by approximating Basic Block Vectors (BBVs) by sampling conditional branches, made possible by PEBS. The algorithm operates on real-hardware, online, and uses fixed 100M instruction count windows. They show that while conditional branches encapsulate less information that all branches, when you are sampling, conditional branches provide better information. They evaluate their phase detection algorithms using the coefficient of variation, comparing the CoV within a phase to the global CoV. They additionally provide a metric which penalizes creating new phases. Finally, they utilize a Markov Predictor, similar to Sherwood and show accurate phase prediction as well. Overall, this paper does an excellent job of solving many off the challenges of phase detection: Feasible with real hardware with a low overhead of less than 2% Address ...