The SPLASH-2 programs: characterization and methodological considerations
ISCA '95 Proceedings of the 22nd annual international symposium on Computer architecture
RSIM: Rice simulator for ILP multiprocessors
ACM SIGARCH Computer Architecture News
HLS: combining statistical and symbolic simulation to guide microprocessor designs
Proceedings of the 27th annual international symposium on Computer architecture
Scientific Computing
Automatically characterizing large scale program behavior
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Complete Computer System Simulation: The SimOS Approach
IEEE Parallel & Distributed Technology: Systems & Technology
Using SimPoint for accurate and efficient simulation
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
MASCOTS '98 Proceedings of the 6th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems
SMARTS: accelerating microarchitecture simulation via rigorous statistical sampling
Proceedings of the 30th annual international symposium on Computer architecture
The Cell Processor Architecture
Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture
Multifacet's general execution-driven multiprocessor simulator (GEMS) toolset
ACM SIGARCH Computer Architecture News - Special issue: dasCMP'05
MonteSim: a Monte Carlo performance model for in-order microachitectures
ACM SIGARCH Computer Architecture News - Special issue on the 2005 workshop on binary instrumentation and application
Ultra-Fast CPU Performance Prediction: Extending the Monte Carlo Approach
SBAC-PAD '06 Proceedings of the 18th International Symposium on Computer Architecture and High Performance Computing
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One of the challenges in the design of multicore architectures concerns the fast evaluation of hardware design-tradeoffs using simulation techniques. Simulation tools for multicore architectures tend to have long execution times that grow linearly with the number of cores simulated. In this paper, we present two hybrid techniques for fast and accurate multicore simulation. Our first method, the Monte Carlo Co-Simulation (MCCS) scheme, considers application phases, and within each phase, interleaves a Monte Carlo modeling scheme with a traditional simulator, such as Simics. Our second method, the Curve Fitting Based Simulation (CFBS) scheme, is tailored to evaluate the behavior of applications with multiple iterations, such as scientific applications that have consistent cycles per instruction (CPI) behavior within a subroutine over different iterations. In our CFBS method, we represent the CPI profile of a subroutine as a signature using curve fitting and represent the entire application execution as a set of signatures to predict performance metrics. Our results indicate that MCCS can reduce simulation time by as much as a factor of 2.37, with a speedup of 1.77 on average compared to Simics. We also observe that CFBS can reduce simulation time by as much as a factor of 13.6, with a speedup of 6.24 on average. The observed average relative errors in CPI compared to Simics are 32% for MCCS and significantly lower, at 2%, for CFBS.