Slack Redistribution for Graceful Degradation Under Voltage Overscaling

Transcription

1 Slack Redistribution for Graceful Degradation Under Voltage Overscaling Andrew B. Kahng, Seokhyeong Kang, Rakesh Kumar and John Sartori VLSI CAD LABORATORY, UCSD PASSAT GROUP, UIUC UCSD VLSI CAD Laboratory and UIUC PASSAT Group - ASPDAC, Jan. 21, 2010

2 Outline Background and motivation Voltage scaling and BTWC designs Limitation of Traditional CAD Flow Power-Aware Slack Redistribution Our design optimization goal Related work: BlueShift Our Heuristic Experimental Framework and Results Design methodology Testbed Results and analysis Conclusions and Ongoing Work (2/25)

3 Reducing Power with Voltage Scaling Power is a first-order design constraint Voltage scaling can significantly reduce power Voltage scaling may result in timing violations Power Timing errors begin to occur Voltage (lower voltage) Voltage scaling is limited because of timing errors (3/25)

4 Better-Than-Worst-Case Design Better-Than-worst-case (BTWC) design approach Optimize for normal operating conditions Trade off reliability and power/performance Have error detection/correction mechanism (e.g., Razor*) Traditional IC design Does not allow timing errors in STA Fixed target frequency and operating voltage BTWC design Error correction architecture allows timing errors CPU, Heal Thyself... Overclocking or voltage overscaling * Ernst et al. Razor: A low power pipeline based on circuit-level timing speculation, Proc. MICRO BTWC design allows tradeoffs between reliability and power (4/25)

5 Voltage Scaling with Error Correction Error correction incurs power overhead Minimum power at point b A B B A Voltage v pwr(v) : Power consumption at v Voltage v P E (v) : Error rate at voltage v Overscaling is possible for Better-Than-Worst-Case designs (5/25)

6 Limitations of Traditional CAD Flow Conventional designs exhibit critical operating points Many paths have near-critical slack wall of (critical) slack Scaling beyond COP causes massive errors that cannot be corrected Conventional designs fail critically when voltage is scaled down Zero slack wall of slack Timing slack Error rate should be increased gracefully : gradual slope slack COP Lower voltage Higher frequency (6/25)

7 Outline Background and motivation Voltage scaling and BTWC designs Limitation of Traditional CAD Flow Power-Aware Slack Redistribution Our design optimization goal Related work: BlueShift Our Heuristic Experimental Framework and Results Design methodology Testbed Results and analysis Conclusions and Ongoing Work (7/25)

8 Our Design Optimization Goal Problem: Minimize power for a given error rate Goal: Achieve a gradual slope slack distribution Approach: Frequently-exercised paths: upsize cells Rarely-exercised paths: downsize cells wall of slack Number of paths gradual slope slack with gradual failure characteristic Zero slack after voltage scaling We make a gradual slope slack distribution Timing slack (8/25)

9 Related Work: BlueShift BlueShift* : maximize frequency for a given error rate Gate-level simulation BlueShift speed up Paths with the highest frequency of timing errors FBB (forward body-biasing) & Timing override Limitation Compute error rate ER < Target Finish * Grescamp et al. Blueshift: Designing processors for timing speculation from the ground up, HPCA 2009 YES Repetitive gate level simulation impractical Design overhead of FBB NO Speed up paths BlueShift is impractical with modern SOC designs (9/25)

10 Our Heuristic Optimize slack distribution by cell swaps, exploiting switching activity information Iteratively scale target voltage the until error rate exceeds a target, and optimize negative slack paths Set initial voltage Optimize Paths Error rate estimation ER < ER target NO Power Reduction Voltage scaling YES Finish Our heuristic: Voltage scaling Optimize paths Power reduction (10/25)

11 Heuristic Implementation Voltage Scaling Set initial voltage Optimize Paths Error rate estimation ER < ER target NO Power Reduction Voltage scaling YES Finish Negative Slack of Path A at the target voltage Nominal voltage Target voltage (fixed) Path A Path B Path C Actual voltage at the target error rate Unnecessary cell sizing Target voltage (fixed) Lower Optimize voltage with fixed incrementally target voltage Load a pre-characterized library at each voltage point With iterative voltage scaling, we can find minimum operating voltage (11/25)

12 Heuristic Implementation Optimize Paths Set initial voltage Optimize Paths Error rate estimation ER < ER target NO Power Reduction Voltage scaling YES Finish Main idea: increase slack of frequently-exercised paths in order of increasing switching activity Procedure 1. Pick a critical path p with maximum switching activity 2. Resize cell instance c i in p 3. If slack of path p is not improved, cell change is restored 4. Repeat 2. ~ 3. for all cell instances in path p 5. Repeat 2.~ 4. for all critical paths OptimizePaths procedure reduces error rates and enables further voltage scaling (12/25)

13 Heuristic Implementation Power Reduction Set initial voltage Optimize Paths Voltage scaling Error rate estimation ER < ER target Main idea: Downsize cells on rarely-exercised paths in order of decreasing toggle rate Procedure 1. Pick a cell c with minimum toggle rate 2. Downsize cell c with logically equivalent cell 3. Incremental timing analysis and check error rate 4. If error rate is increased, cell change is restored 5. Repeat 1. ~ 4. YES NO Power Reduction Finish PowerReduction procedure reduces power without affecting error rate (13/25)

14 Heuristic Implementation Error Rate Estimation Set initial voltage Optimize Paths Error rate estimation ER < ER target NO Power Reduction Voltage scaling YES Finish Error rate estimation: use toggle rate from SAIF(Switching Error Activity rate Interchange contribution Format) Error rate of an entire design of one flip-flop P 1 ER = α TG = TG A ER ff f/f TG(P 1 ) = 0.3 TG(P 2 ) = 0.2 TG(P 3 ) = 0.1 TG(X) = 0.6 D ER ff CLK P 2 X PNEG ff D ff X P 3 TGf/f PALL P 1 P 2 P 1 P 2 P 1 P 3 Slack(P 1 ) = postive Slack(P 2 ) = negative Slack(P 3 ) = positive ER(X) = TG(X) α : compensation parameter Timing Error We estimate error rates without functional simulation TG(P 2 ) TG(P 1 ) + TG(P 2 ) + TG(P 3 ) = 0.2 (14/25)

15 Power Reduction Through Slack Redistribution Power Minimum power P min is obtained at minimum operating voltage V min 1. OptimizePaths Minimize error rate Enable to scale voltage further 2. ReducePower Downsize cells Obtain additional power reduction P min P min P min Power consumption Operating point V min Error rate Error rate Operating 1. OptimizePaths point 1 Maximum error rate 2 Operating point 2. ReducePower V min (lower voltage) (15/25)

16 Outline Background and motivation Voltage scaling and BTWC designs Limitation of Traditional CAD Flow Power-Aware Slack Redistribution Our design optimization goal Related work: BlueShift Our Heuristic Experimental Framework and Results Design methodology Testbed Results and analysis Conclusions and Ongoing Work (16/25)

17 Design Methodology Functional Library ECO Benchmark Heuristic P&R characterization (Slack simulation generation Optimization) Cadence Virtutech Implement NC SignalStorm SOCEncounter Simics in Verilog C++ and Full system Gate use Synopsys ECO Tcl level implementation socket simulation Liberty interface and generation capture with for test each vectors Synopsys voltage PrimeTime (17/25)

18 Testbed Target design : sub-modules of OpenSPARC T1 Benchmark Ammp, bzip2, equake, sort and twolf Make test vectors with 1 billion cycles for each sub-module Implementation TSMC 65GP technology with standard SP&R flow (18/25)

19 List of Experiments Design techniques 1. SP&R with 0.8 GHz (loose constraints) 2. SP&R with 1.2 GHz (tight constraints) 3. Blueshift: timing override 4. Slack Optimizer Experiments compare all design techniques with respect to: 1. Power consumption at each voltage point 2. Actual error rates from gate level simulation 3. Power consumption at each target error rate 4. Estimated processor-wide power consumption (19/25)

20 Error Rate and Power Results Error rate at each operating voltage (test case : lsu_dctl) Power consumption at each operating voltage (20/25)

21 Comparison of Power and Slack Results Power consumption at each target error rate Slack distribution (21/25)

22 Power Reduction and Area Overhead Power reduction after optimization 2% error rate) Area overhead of design approaches Max %, Avg. 12.5% power reduction (22/25)

23 Processor-wide Results * *Kahng et al. Designing a Processor From the Ground Up to Allow Voltage/Reliability Tradeoffs, HPCA Slack optimization extends range of voltage scaling and reduces Razor recovery cost (23/25)

24 Conclusions and Ongoing Work Showed limitations of a BTWC design Presented design technique slack redistribution Optimize frequently exercised critical paths De-optimize rarely-exercised paths Demonstrated significant power benefits of gradual slack design Reduced power 33% on maximum, 12.5% on average Ongoing work Reliability-power tradeoffs for embedded memory Applying to heterogeneous multi-core architecture (24/25)

25 THANK YOU UCSD VLSI CAD Laboratory and UIUC PASSAT Group - ASPDAC, Jan. 21, 2010

26 BACKUP UCSD VLSI CAD Laboratory and UIUC PASSAT Group - ASPDAC, Jan. 21, 2010

27 CPU, Heal Thyself Razor* system Timing errors can be corrected Manage the trade-off between system voltage and error rate New design methodology is needed * Razor: A low power pipeline based on circuit-level timing speculation. In International Symposium on Micro architecture, December (27/25)

28 Razor How it works Razor Implementation Razor: A low power pipeline based on circuit-level timing speculation. In International Symposium on Microarchitecture, December Main flip-flop latches at T, but Shadow latch latches at T+skew If a timing violation occurs, main flip-flop will latch incorrect value, but shadow latch should latch correct value Comparator signals error and the late arriving value is fed back into the main flip-flop (28/25)

29 BTWC: Voltage Scaling Voltage Overclocking scaling case case PE(f) perf(f) Minimum Maximum power performance at point c b c a c b c a b vf vf vf a vf b vf c (lower voltage) vf a vf b vf c P E (v) (f) : Error rate at frequency voltage v f pwr(v) perf(f) : Performance Power consumption at f at v Error correction needs additional clock cycles and incurs power overhead (29/25)

30 Limitation of Voltage Scaling At some voltage, circuit breaks down Errors / Cycle Voltage Voltage scaling must halt after only 10% scaling. (30/25)

31 Reason for Steep Error Degradation Critical paths are bunched up in traditional designs. (31/25)

32 Slack Re-distribution Example Negative Positive Slack Error Rate = 1% 25% Negative Positive Slack (32/25)

33 Heuristic Implementation Error Rate Estimation Error rate contribution of one flip-flop (1) ER = Error rate of an entire design ER ff TG = α (2) α : compensation parameter Actual vs. estimated error rates ff TG D ER ff ff D TG P P NEG ALL (33/25)

34 Gradual Slack Distribution Slack optimization achieves gradual slack distribution. (34/25)

35 Processor Error Rate and Power Designs with comparable error rates have much higher power/area overheads. (35/25)

36 Reliability/Power Tradeoff Slack-optimized design enjoys continued power reduction as error rate increases. (36/25)

37 Enhancing Razor-based Design Slack optimization extends range of voltage scaling and reduces Razor recovery cost. (37/25)

38 Moore s Law Power consumption of processor node doubles every 18 months. (38/25)

39 Power Scaling With current design techniques, processor power soon on par with nuclear power plant (39/25)