Power and Performance of Native and Java Benchmarks on 130nm to 32nm Process Technologies

Hadi Esmaeilzadeh (1) , Stephen M. Blackburn (2) , Xi Yang (2) , Kathryn S. Mckinley (1)

1 University of Texas at Austin [Austin]
2 ANU - Australian National University

Over the past decade, chip fabrication technology shrank from 130nm to 32nm. This reduction was generally considered to provide performance improvements together with chip power reductions. This paper examines how well process technology and microarchitecture delivered on this assumption. This paper evaluates power and performance of native and Java workloads across a selection of IA32 processors from five technology generations (130nm, 90nm, 65nm, 45nm, and 32nm). We use a Hall effect sensor to accurately measure chip power. This paper reports a range findings in three areas. 1) Methodology: TDP is unsurprisingly a poor predictor of application power consumption for a particular processor, but worse, TDP is a poor predictor of relative power consumption between processors. 2) Power-performance trends: Processors appear to have already hit the power wall at 45nm. 3) Native versus Java workloads and their relationship to processor technology: Single threaded Java workloads exploit multiple cores. These results indicate that Java workloads offer different opportunities and challenges compared to native workloads. Our findings challenge prevalent methodologies and offer new insight into how microarchitectures have traded power and performance as process technology shrank.

Domaines: Autre [cs.OH]

Hadi Esmaeilzadeh, Stephen M. Blackburn, Xi Yang, Kathryn S. Mckinley. Power and Performance of Native and Java Benchmarks on 130nm to 32nm Process Technologies. MoBS 2010 - Sixth Annual Workshop on Modeling, Benchmarking and Simulation, Jun 2010, Saint Malo, France. ⟨inria-00492998⟩