Jiwon Hahn ECE295 Seminar December 2, 2002 Integrated Management of Power Aware Computing & Communication Technologies

IMPACCT Project People Faculty: Pai Chou, Nader Bagherzadeh Students: Jinfeng Liu, Dexin Li, Bita Gorji-Ara, Duan Tran, and Jiwon Hahn Collaborator NASA JPL, Rockwell Collins, ISI Sponsors DARPA PAC/C, Broadcom, HP

Outline What is IMPACCT? Motivation How it works Tools Experiments and Results Conclusions and Future Works

What is IMPACCT? A CAD tool for exploring power/performance tradeoffs A new technique that performs component, system, and mission-level integrated power management Target applications Mars pathfinder, ATR, UCAV,…

Motivation Embedded Systems Computers inside devices PDA, cellphone, camera, vehicles, robots,… Power management Power-Aware vs. Low-power Mission-Aware: meet the constraints High-level approach Amdahl’s law: Power saving of a component must be scaled by its percentage contribution to entire system Evaluate combined effects in the context of system Higher abstraction level enables global optimum

How it works Hierarchical power management System-level power scheduling Power-aware scheduling Mode selection Mission-level power scheduling Schedule Selection

Scheduling & Mode Selection Power Aware Scheduling Schedules tasks, meeting timing and power constraints Output: initial schedule Static scheduling/planning [DAC'01] Mode Selection Selects resource modes of each task considering mode dependency Minimize energy consumption Output: mode schedule Mode selection/modeling [ASPDAC’02] Winner Best Student Paper Award

Schedule Selection Goal To generate a mission level schedule which Adapts to variable power constraint Considers higher-level context change overhead Meets the global deadline Assumptions A mission contains one or more applications It is static

Schedule Selection Problem: Select N schedules among M different schedules, by deadline D, under the maximum power curve P. Minimize energy considering overhead … M … Schedule Set D P Put N schedules here! 01…M 0 1 … M Overhead Matrix Current schedule Previous Schedule

Schedule Selection(cont.) Parameters: t,n,k,m t: timestamp. (discrete value) 0  t  D n: schedule count excluding S 0 1  n  N k: schedule count including S 0. (for tracking the selected path) 1  k  D m:current schedule0  m  M

Schedule Selection(cont.) Algorithm: 4D Dynamic Programming n k m t = D t =2 t =1 n m t  Idea:  Reach the global optimum by keeping track of optimal solutions of subproblems  Optimal substructure  For some(k,m), min{E(t,n,m)} contains the optimal value.  Space  D 3 for keeping optimal Energy  D 4 for bookkeeping indices  Speed  O(D 3 ) – polynomial!  Could be optimized for speed-up Energy Cube Bookkeeping Cubes

Schedule Selection(cont.) Notation Set of schedule, S= {S 0, S 1, …, S M } Time period of each schedule: Ts[0…M] Power level of each schedule: Ps[0…M] Energy of each schedule: Ts x Ps = Es[0…M] Schedule-switch overheads from S i to S j : Po(i,j), To(i,j), Eo(i,j)

Schedule Selection(cont.) Algorithm Initialization If (t,n,k,m) is the first possible selection, E(t,n,k,m) = directly calculated energy Else E(t,n,k,m) =  Process if m!=0, E(t,n,k,m)=E(t’,n-1,k-1,m’)+Eo(m’,m)+Ps(m)Ts(m) t = t’+To(m’,m)+Ts(m) if m=0, E(t,n,k,m)= E(t’,n,k-1,m’)+Eo(m’,m)+Ps(m)Ts(m)

System-level Input: Application Model ports, channels,… Architecture Model System architecture template Component library + mode dependency model(MDM) Constraints Power and Timing Output: Mode Schedule  Mission-Level Mission-level Constraints: Power and Deadline Mission Schedule

System-level 1 App. ModelConstraints Sys. Arch. Template Component Library + MDM Mode Schedule 1) Schedule Selector  Mission-Level 2 Mission Constraints Overhead Calculator Mission Schedule MS … Schedule Collector 2 Scheduler Initial Schedule Mode Selector 1

System-level Initial Schedule: Mode Schedule:  Mission-Level Mission Power Constraint Curve Mission Deadline Mission Schedule:

Tools Scheduler (Jinfeng) Mode Selector (Dexin) Schedule Selector (Jiwon) Etc.. Programs and tutorial are available

Tools(I): Scheduler

Tools(II): Mode Selector

Tools(III): Schedule Selector

Mars Rover Comparison over 3 scenarios Overall mission 3 power scenarios: best, typical, worst, 10 min each 48 steps Power-aware schedules Accelerated speed by tracking available power Finished earlier before working in the worst case 33% faster, 32.7% less energy cost Experiments and Results I

Experiments and Results I(cont.)

Experiments and Results II Mars Rover Behaviors and tasks Moving around on Mars surface Communicating with the Lander Taking pictures Performing scientific experiments Components in the entire system Hazard detector, Driving motor, Steer motor, Radio frequency modem (RF), Camera (CAM), Microprocessor (PPC), Micro-controller

Experiments and Results II(cont.) On/off only Relaxed constraints Mode change overhead No max power constraint Mode selection Energy saving: From 6.9% to 49.3% average 26.5% Meets max power

Experiments and Results III Example of Schedule Selection s 3s 4s 0J4J7J 6J 0W4W21W 24W 1 ? 1s ? ? 4J 4W 2 ? 2s ? ? 5J 10W 3 ? 3s ? ? 10J 30W 20s s, 5J, 50W 5s, 10J, 50W 3s, 15J, 45W Schedule Set: Overhead Matrix

Experiments and Results III(cont.) s Low Power Greedy Dynamic Programming Exceed deadline Energy = 149W Nonoptimal solution Energy = 131W Optimal solution!

Experiments and Results III(cont.) Run-timeDeadline Guarantee Energy optimization ManualN/AXX Low PowerconstantXX GreedylinearXX EnumerationexponentialOO Dynamic Programming polynomialOO

Conclusions IMPACCT greatly expands the range of power/performance trade-offs effectively integrates existing power management techniques models system-level dependencies saves great amount of energy consumption while meeting all constraints proposes novel hierarchical power management technique

Current & Future Works Ongoing work Architecture Modeling(Dexin) Mission-level Power Management(Jiwon) Extended experiments on broadcom and itsy board(Jinfeng) Applying to different application: SDR(Bita) Future work Dynamic Power Management Mixed application schedule selection More applications

Reference Pai H. Chou, Jinfeng Liu, Dexin Li, and Nader Bagherzadeh, “IMPACCT: Methodology and Tools for Power-Aware Embedded Systems”, Design Automation for Embedded Systems J. Liu, P. Chou, N. Bagherzadeh, and F. Kurdahi. “Power-aware scheduling under timing constraints for mission-critical embedded systems”. In Proc. 38th Design Automation Conference, pages 840– 845, June 2001 D. Li, P. Chou, and N. Bagherzadeh. Mode selection and mode- dependency modeling for power-aware embedded systems. In Proc. 7th Asia South Pacific Design Automation Conference, pages 697– 704, January 2002 J. Hahn, P. Chou, and N. Bagherzadeh, “Tutorial: IMPACCT Tool v1.0”, University of California at Irvine, August, 2002 THANK YOU!