Performance Analysis and Power Estimation of ARM processor
Performance Analysis and Power Estimation of ARM Processor Team: Ajayshanker Krishnamurthy Swathi Tanjore Gurumani Zexin Pan Project Advisor: Dr.Alexander Milenkovic Apr 14,2003 CPE 631 Project Agenda Overview Tools Used Performance Analysis - Results Power Estimation - Results Conclusion Apr 14,2003 CPE 631 Project
Overview Target Binaries Performance Metrics Simulator Benchmarks Compile Exe Power Estimator Performance Metrics MiBench SimpleScalar PowerAnalyzer Apr 14,2003 Power
Dissipated CPE 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 Automotive and Industrial Control, Network, Security, 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
Apr 14,2003 CPE 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 Supports popular instruction sets -Alpha, Power PC, x86 & ARM Baseline simulator models: - Sim-safe, Sim-fast, Sim-cache, Sim-profile, Sim-bpred, Sim-fuz, Sim-outorder Apr 14,2003 CPE 631 Project Tools Used 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 & Empirical Apr 14,2003 CPE 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
Apr 14,2003 CPE 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 Apr 14,2003 CPE 631 Project Configuration
Current Next I Fetch Q size 2 4 Branch Pred. Not Taken Bimod I Issue Width 1 1 Cache dl1
RCD RND BFCE BFNE BFCD BFND SHAC SHAN Current generation predictor : Not Taken Next generation predictor Apr 14,2003 CPE 631 Project : Bimod
Results % of Branches 7 6 Branches 5 4 3 2 1 0 Apr 14,2003 CPE 631 Project Why use power as performances 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 Apr 14,2003 CPE 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 Apr 14,2003 CPE 631 Project Power Estimation 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 ?? Apr 14,2003 CPE 631 Project Power Estimation Pow er distribution of Intel XScale using Rijndael Power distribution of Intel StrongARM SA- aio 110 using Rijndael dio dio irf irf il1
il1 dl1 dl1 itlb itlb Power distribution of StrongARM SA-110 using Blowfish Apr 14,2003 aio dtlb dtlb bimod
clock clock uarch uarch Power distribution of Intel XScale using Blowfish aio aio dio dio irf irf il1 il1
Power Estimation Billions Power Total Power vs. Benchmark 15 10 5 0 SA-110 XScale Benchmark in Security Apr 14,2003 CPE 631 Project Power Estimation
Thousands Power per Byte Power consumption per Enc/Des byte 5 4 3 2 1 0 SA-110 XScale Behchmark in Security Apr 14,2003 CPE 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 Apr 14,2003 CPE 631 Project Thank You Questions Apr 14,2003 CPE 631 Project
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