1. Apr 14,2003CPE 631 Project Performance Analysis and Power Estimation of ARM Processor Team: Ajayshanker Krishnamurthy Swathi Tanjore Gurumani Zexin Pan Project Advisor: Dr.Alexander Milenkovic

2. Apr 14,2003CPE 631 Project Agenda Overview Tools Used Performance Analysis - Results Power Estimation - Results Conclusion

3. Apr 14,2003CPE 631 Project Overview MiBench SimpleScalar PowerAnalyzer Power Dissipated Target Binaries Benchmarks Exe Compile Simulator Power Estimator Performance Metrics Performance Metrics

4. Apr 14,2003CPE 631 Project Tools Used Benchmarks: Critical part of design process due to performance based designs Embedded Benchmarks:Fastest growing market segment in the u-processor industry MiBench: (University of Michigan) Free, commercially representative embedded benchmark suite Set of 35 embedded applications of six categories Security –Automotive and Industrial Control, Network, Security, Consumer Devices, Office Automation and Telecommunications Security Algorithms– Rijndael, Blowfish, Sha, Pgp Small data set represents a light-weight, useful embedded application Large data set provides a more stressful, real-world application

5. Apr 14,2003CPE 631 Project Tools Used… SimpleScalar SimpleScalar: (Born 1982, @ University of Wisconsin) Provides an infrastructure for simulation and architectural modeling Can model a variety of platforms - unpipelined processors to detailed micro architectures Suited to the needs of researchers and instructors - meets the critical requirements: Performance, Flexibility & Detail ARM Supports popular instruction sets -Alpha, Power PC, x86 & ARM Baseline simulator models: - Sim-safe, Sim-fast, Sim-cache, Sim-profile, Sim-bpred, Sim-outorder Sim-fuz, Sim-outorder

6. Apr 14,2003CPE 631 Project Tools Used… PowerAnalyzer: PowerAnalyzer: SimpleScalar-Arm Power Modeling Project Joint venture of U Michigan & U Colorado Estimator that allows power/performance trade-offs to be examined Tightly Coupled with SimpleScalar Toolset for ARM Gives Power dissipation for each component individually –Switching, Internal &Leakage Can be configured based on two models: –Analytical –Analytical & Empirical

7. Apr 14,2003CPE 631 Project Measurement Methodology Configured for Current (SA 110) and Next (PXA 250) generation Input: Same dataset (>3M) for all algorithms to achieve fair comparison and reliable result Output: raw data related to performance and power consumption are obtained from PowerAnalyzer report Data Processing (digesting) and visualizing

8. Apr 14,2003CPE 631 Project Performance Analysis Configured Sim-outorder to represent current and next generation of embedded processors Intel SA-110 for current generation –32 bit general purpose micro processor –On chip data cache(16K),instruction cache(16 K) and MMU –Used in PDAs, Smart phones, digital cameras etc. Intel PXA-250 for next generation –High performance Intel Xscale core –On chip data cache(32 K),instruction cache(32 K),branch target buffer and MMU –Used in Multimedia Applications

9. Apr 14,2003CPE 631 Project Configuration CurrentNext I Fetch Q size24 Branch Pred.Not TakenBimod I Issue Width11 Cache dl116:32:3232:32:32 Cache il116:32:3232:32:32 TLB itlb16:4096:4 TLB dtlb32:4096:4

10. Apr 14,2003CPE 631 Project Results

11. Apr 14,2003CPE 631 Project Results

12. Apr 14,2003CPE 631 Project Results Current generation predictor : Not Taken Next generation predictor : Bimod

13. Apr 14,2003CPE 631 Project Results

14. Apr 14,2003CPE 631 Project Why use power as performance’s criteria? T. Mudge, “Power: A first class design constraint,” Computer, vol. 34, no. 4, April 2001, pp. 52-57 – Limiting power consumption is critical, particularly in portable and mobile applications such as cell phone and laptop due to limit battery life –One of the major markets of ARM is portable and mobile products

15. Apr 14,2003CPE 631 Project Power Estimation Measurement Methodology –ARM simulator & power measurement tools: PowerAnalyzer 1.1 from UMICH –Configured for Current (SA 110) and Next (PXA 250) generation –Input: Same dataset (>3M) for all algorithms to achieve fair comparison and reliable result –Output: raw data related to performance and power consumption are obtained from Power Analyzer report –Data processing (digesting) and visualizing

16. Apr 14,2003CPE 631 Project Difficulties using PowerAnalyzer –Report gives power consumption for every ARM component, but no unit! –Since all these numbers are huge, we have difficulties figuring out what they mean ?? Power Estimation

17. Apr 14,2003CPE 631 Project Power Estimation

18. Apr 14,2003CPE 631 Project Power Estimation

19. Apr 14,2003CPE 631 Project Power Estimation

20. Apr 14,2003CPE 631 Project Conclusion The performance gain in next generation of processors is offset by the increase in power consumption. Intel Xscale almost doubles the power consumption with about 10% performance gain over SA- 110 The next generation of processors with larger caches improve performance The bimodal branch predictor greatly reduces the number of miss predictions Power consumption not only depends on hardware architecture and system configuration (system clock,etc.), but also heavily relies on Benchmark and input dataset

21. Apr 14,2003CPE 631 Project Thank You Questions…