COOPERATIVE CROSS-LAYER PROTECTION FOR RESOURCE CONSTRAINED MOBILE MULTIMEDIA SYSTEMS

Transcription

1 COOPERATIVE CROSS-LAYER PROTECTION FOR RESOURCE CONSTRAINED MOBILE MULTIMEDIA SYSTEMS Prof. Nikil Dutt Prof. Nalini Venkatasubramanian Prof. Lichun Bao Nov. 26, 2008 Kyoungwoo Lee (final defense)

2 2 Contents Thesis Motivation Thesis Proposal Cooperative, Cross-layer Methods PPC (Partially Protected Caches) EAVE (Error-Aware Video Encoding) CC-PROTECT (Cooperative, Cross-layer Protection) Thesis Contribution and Future Direction

3 3 Mobile Multimedia Embedded Systems 3D Graphics Resource-limited Image Browsing mobile devices! Map Routing Main problem is to achieve low power with high performance, high QoS, and high reliability Mobile TV Animation Web Browsing Satellite TV Video Streaming Video Conferencing

4 4 Reliability Reliability is an emerging and critical concern in mobile devices New enhanced technology makes devices vulnerable to errors due to high complexity and high integration Exponential increase of soft error rate as technology scales [Baumann, 05] Mobile applications are running close to humans In pervasive computing, failures of healthcare mobile devices cause serious results Redundancy techniques incur high overheads of power and performance TMR (Triple Modular Redundancy) may exceed 200% overheads without optimization [Nieuwland, 06] Challenging to optimize multiple properties (e.g., performance, power, QoS, and reliability) in mobile embedded systems

5 5 Soft error is becoming an every second concern! Soft Error Rate (SER) FIT (Failures in Time) = number of errors in 10 9 hours SER (FIT) MTTF Reason µm years µm 64x8x days High Integration nm 2x1000x64x8x hour Technology scaling and Twice Integration A 65 nm 2x2x1000x64x8x minutes Memory takes up 50% of soft errors in a system A system with voltage 65 nm A system with voltage flight (35, nm 100x2x2x1000x64x8x x100x2x2x1000x6 4x8x1000 FIT 18 seconds Exponential relationship b/w SER & Supply Voltage 0.02 seconds High Intensity of Neutron Flux at flight (high altitude)

6 6 Errors and Failures in Mobile Embedded Systems Faults or Errors can cause Failures Exce ption Bug Application Middleware/ OS Hardware Soft Error Packet Loss Network

7 7 Errors and Error Control Schemes at Hardware Application MW/ OS Network Hardware Failures Causes Metrics Traditional Approaches Soft Errors, Hard Failures, System Crash External Radiations, Thermal Effects, Power Loss, Poor Design, Aging FIT, MTTF, MTBF Spatial Redundancy (TMR, Duplex, RAID-1 etc.) and Data Redundancy (EDC, ECC, RAID-5, etc.) Hardware failures are increasing as technology scales (e.g.) SER increases by up to 1000 times [Mastipuram, 04] Redundancy techniques are expensive (e.g.) ECC-based protection in caches can incur 95% performance penalty [Li, 05] FIT: Failures in Time (10 9 hours) MTTF: Mean Time To Failure MTBF: Mean Time b/w Failures TMR: Triple Modular Redundancy EDC: Error Detection Codes ECC: Error Correction Codes RAID: Redundant Array of Inexpensive Drives

8 8 Errors and Error Control Schemes at Software Application MW/ OS Network Hardware Failures Causes Metrics Traditional Approaches Wrong outputs, Infinite loops, Crash Incomplete Specification, Poor software design, Bugs, Unhandled Exception Number of Bugs/Klines, QoS, MTTF, MTBF Spatial Redundancy (Nversion Programming, etc.), Temporal Redundancy (Checkpoints and Backward Recovery, etc.) Software errors become dominant as system s complexity increases (e.g.) Several bugs per kilo lines Hard to debug, and redundancy techniques are expensive (e.g.) Backward recovery with checkpoints is inappropriate for real-time applications QoS: Quality of Service

9 9 Errors and Error Control Schemes in Networks Application MW/ OS Network Hardware Failures Causes Metrics Traditional Approaches Data Losses, Deadline Misses, Node (Link) Failure, System Down Network Congestion, Noise/Interferenc e, Malicious Attacks Packet Loss Rate, Deadline Miss Rate, SNR, MTTF, MTBF, MTTR Network is unreliable (especially, wireless networks) Joint approaches across OSI layers have been investigated for minimal costs [Vuran, 06][Schaar, 07] Resource Reservation, Data Redundancy (CRC, etc.), Temporal Redundancy (Retransmission, etc.), Spatial Redundancy (Replicated Nodes, MIMO, etc.) SNR: Signal to Noise Ratio MTTR: Mean Time To Recovery CRC: Cyclic Redundancy Check MIMO: Multiple-In Multiple-Out

10 10 Conventional Approaches Most redundancy techniques incur overheads in terms of performance, power, area, etc. Conventional TRM (Triple Modular Redundancy) can incur 200% overheads without optimization. Backward Recovery with Checkpoints cannot guarantee the completion time of a task. Recently proposed techniques have focused on the cost reduction without losing reliability However, they still incur overheads

11 11 Thesis Problem Statement Study tradeoffs among system properties (e.g.) Redundancy incurs energy overheads while DVS increases SER significantly Examine errors and error control schemes across system abstraction layers (e.g.) network errors & error-resilient video encoding, soft errors & ECC or EDC, etc. Maximize reliability with minimal costs of power and performance for mobile embedded systems

12 12 Cross-Layer Methods Cross-layer approaches: aim at system-level optimization Integrate and coordinate techniques across system layers Classification [Srivastava, 05] Top-down, Bottom-up, or Both direction Top-down PPC, PDVS [GRACE], etc. Bottom-up EAVE, etc. Both direction CC-PROTECT, etc. Coupling or Merging layers Dynamo [Mohapatra], xtune [Kim], etc. Coupling Merging Bottom-up Top-down

13 13 Cross-Layer Approaches GRACE GRACE UIUC [W. Yuan Ph.D. thesis in 04 and A. F. Harris III, Ph.D. thesis in 06] QoS/Power tradeoffs Primarily OS adaptation for power management in multimedia mobile devices Network adaptation for power management in multimedia communications [GRACE, 05] Application Operating System Hardware

14 14 Cross-Layer Approaches DYNAMO & FORGE DYNAMO middleware for FORGE UCI [S. Mohapatra Ph.D. thesis in 05 and R. Cornea Ph.D. thesis in 07] QoS/Power tradeoffs for mobile embedded systems Middleware-driven coordination and proxy-based cooperation 1. Content transcoding at the application layer 2. Network traffic shaping at the network layer 3. Backlight (LCD display) setting at the hardware layer 4. NIC shutdown, CPU DVS/DFS at the hardware layer 1 Proxy Server (NW & MW) 2 Application Middleware/ OS 3 4 Hardware

15 15 Cross-Layer Approaches xtune xtune UCI and SRI [M. Kim Ph.D. thesis in 08] QoS/Power/Timeliness adaptation for distributed real-time embedded systems A Formal Methodology for cross-layer tuning and verifiable timeliness of Mobile Embedded Systems Application Middleware/ OS Proxy Server Handheld Server Hardware

16 16 Thesis Proposed Contribution Thesis proposes a cross-layer design methodology for mobile multimedia embedded systems with minimal costs Reliability/QoS/Power/Performance system optimization for mobile multimedia systems Cooperative, Cross-Layer Protection PPC, EAVE, & CCPROTECT Low-cost reliability

17 17 Overview of Thesis Proposals Mobile Video Application Error-prone Networks Original Video Multimedia Application Error-Controller (e.g., frame drop) Unprotected Cache Error-Resilient Encoder (e.g., PBPAIR) EAVE Application Correction Protected Cache EDC ECC QoS Monitor Error-prone & Translate Networks SER MW/OS Mobile Video Application Error detection Hardware Error- Aware Video Frame Drop Packet Loss PPC (Partially Protected Caches) EAVE (Error-Aware Video Encoding) CC-PROTECT (Cooperative, Crosslayer Protection)

18 18 Contents Thesis Motivation Thesis Proposal Cooperative, Cross-layer Methods PPC (Partially Protected Caches) EAVE CC-PROTECT Thesis Contribution and Future Direction Application Middleware/ OS Hardware Network

19 19 Conventional Protection for Caches Conventional Protected Caches Unaware of fault tolerance at applications Implement a redundancy technique such as ECC to protect all data for every access Overkill for multimedia applications ECC (e.g., a Hamming Code) incurs high performance penalty by up to 95%, power overhead by up to 22%, and area cost by up to 25% Unaware of Application High Cost Cache ECC

20 20 PPC (Partially Protected Caches) Observation Not all data are equally failure critical Multimedia data vs. control variables Propose PPC architectures to provide an unequal protection for mobile multimedia systems [Lee, CASES06][Lee, TVLSI08] Unprotected cache and Protected cache at the same level of memory hierarchy Protected cache is typically smaller to keep power and delay the same as or less than those of Unprotected cache PPC Unprotected Cache Memory Protected Cache

21 21 PPC for Multimedia Applications Unprotected Cache Memory PPC Protected Cache Propose a selective data protection [Lee, CASES06] Unequal protection at hardware layer exploiting error-tolerance of multimedia data at application layer Simple data partitioning for multimedia applications Multimedia data is failure noncritical All other data is failure critical Power/Delay Reduction Fault Tolerance

22 22 PPC for General Applications DPExplore [Lee, PPCDIPES08] Explore partitioning space by exploiting awareness of vulnerability of each data page Vulnerable time It is vulnerable for the time when eventually it is read by CPU or written back to Memory Pages causing high vulnerable time are failure critical Vulnerable time closely estimates failure rate data Incoming Read Unprotected Cache Write Memory Eviction t 0 t 1 t 2 t 3 PPC Protected Cache

23 23 Summary PPC All data are not equally failure critical Propose a PPC architecture to provide unequal protection Support an unequal protection at hardware layer by exploiting error-tolerance and vulnerability at application Present cost-efficient reliability Related Publications [Lee, CASES06] PPC for multimedia embedded systems [Lee, PPCDIPES08] PPC for general applications [Lee, TVLSI08] PPC and design space exploration Under submission [Lee, TODAES??] PPC for general applications and instruction caches Application Data & Code Error-tolerance of MM data Vulnerability of Data & Code Page Partitioning Algorithms Failure Non- Failure Critical Critical FNC & FC are mapped into Unprotected & Protected Caches Unprotected Cache PPC Protected Cache

24 24 Contents Thesis Motivation Thesis Proposal Cooperative, Cross-layer Methods PPC EAVE (Error-Aware Video Encoding) CCPROTECT Thesis Contribution and Future Direction Application Middleware/ OS Network

25 25 Active Error Exploitation Intentional Frame Drop Intentional Frame Drop (one way to actively exploit errors) can result in energy reduction for each operation FDT-1 affects the following components with respect to power, performance, and QoS in mobile video applications Enc CPU FDT-1 Tx WNI FDT-2 Error-prone Networks Mobile Video Application Packet Loss Rx WNI Dec CPU FDT-3 FDT: Frame Drop Type Enc: Encoding, Dec: Decoding WNI: Wireless Network Interface

26 26 Error-Aware Video Encoding EIR: Error Injection Rate Propose EE-PBPAIR [Lee, DIPES08] Intentionally drop frames at video encoding Reduce the energy consumption for video encoding Maintain the video quality by exploiting error-resilience of PBPAIR Original Video Intentional frame drop Error-prone Networks Packet Loss Error-Aware Video Encoder (EAVE) Error-Controller (e.g., frame dropping) Error-Resilient Encoder (e.g., PBPAIR) Error- Resilient Aware Video

27 27 Summary EAVE Intentional Frame Drop is one way to exploit errors actively Propose an error-aware video encoding (EE-PBPAIR) Present a knob (EIR) to adjust the amount of errors considering the QoS feedback Maintain the video quality using error-resilience of PBPAIR Related Publication [Lee, DIPES08] EE-PBPAIR Considering Submission [Lee, TECS??] Generalized idea for error-resilient video encodings EIR Error Resilient Video Encoder Application Error Rate = PlR + EIR Error Controller Middleware Energy Reduction CPU, Memory, and WNIC Hardware Error-Aware Video Data PLR & QoS Network or Decoding Side EIR: Error Injection Rate PLR: Packet Loss Rate

28 28 Contents Thesis Motivation Thesis Proposal Cooperative, Cross-layer Methods PPC EAVE CC-PROTECT (Cooperative Cross-layer Protection) Thesis Contribution and Future Direction Application Middleware/ OS Hardware Network

29 29 Errors and Error Control Schemes No Coupling Different errors and their protection techniques have not been considered jointly No coupling and no cooperation Cooperating control schemes in a cross-layer manner can open a new venue Application Middleware/ OS Hardware Error-prone Networks Mobile Video Application Soft Error Packet Loss Network

30 30 PPC still incurs overheads due to ECC-protection Propose PPC architectures to provide an unequal protection for mobile multimedia systems [Lee, TVLSI08] Unprotected cache and Protected cache a the same level of memory hierarchy PPC still incurs overheads due to high expensive ECC-protection at the protected cache 29% energy reduction compared to the protected cache 10% energy overhead compared to the unprotected cache PPC Unprotected Cache Memory Protected Cache

31 31 PBPAIR is energy-inefficient in error-free network PBPAIR is error-resilient and energy-efficient in general PBPAIR may not be energy efficient in case of error-free network network Packet Loss PLR PBPAIR Intra_Threshold PBPAIR: Probability-Based Power Aware Intra Refresh [Kim, 06]

32 32 riginal Video Outline of CC-PROTECT Error-Controller Error-Resilient (e.g., frame drop) Encoder (e.g., PBPAIR) Error-Aware Video Encoder (EAVE) Error- Aware Video QoS Loss Frame Drop Mobile Video Application Error-prone Networks Packet Loss Monitor & Translate SER Feedback Parameter Trigger Selective DFR Error-prone Support EAVE Networks & PPC MW/OS Mobile Video Application BER (Backward DFR (Drop & Error Recovery) Forward Recovery) frame K frame K+1 Unprotected Cache Protected Cache EDC PPC Error detection

33 33 Energy Saving BASE = Error-prone video encoding + unprotected cache HW-PROTECT = Error-prone video encoding + PPC with ECC APP-PROTECT = Error-resilient video encoding + unprotected cache MULTI-PROTECT = Error-resilient video encoding + PPC with ECC CC-PROTECT1 = Error-prone video encoding + PPC with EDC CC-PROTECT2 = Error-prone video encoding + PPC with EDC + DFR CC-PROTECT = error-resilient video encoding + PPC with EDC + DFR EDC + impact DFR + impact PBPAIR(CC-PROTECT) impact 17% 36% 56% Reduction compared to HW-PROTECT 4% 26% 49% Reduction compared to to BASE

34 34 Summary CC-PROTECT Propose CC-PROTECT approach, which cooperates existing schemes across layers to mitigate the impact of soft errors on the failure rate and video quality in mobile video encoding systems PPC (Partially Protected Caches) with EDC (Error Detection Codes) at hardware layer DFR (Drop and Forward Recovery) at middleware PBPAIR (Probability-Based Power Aware Intra Refresh) at application layer Demonstrate the effectiveness of low-cost (about 50%) reliability (1,000x) at the minimal cost of QoS (less than 1%) Related Publication [Lee, ACMMM08] CC-PROTECT Considering Submission [Lee, ACMTOMCCAP??] Tradeoff space exploration with CC-PROTECT Application Middleware/ OS Hardware PBPAIR - Error Resilience DFR - Error Correction Unprotected Cache ECC EDC Protected Cache

35 35 Contents Thesis Motivation Thesis Proposal Cooperative, Cross-layer Methods PPC EAVE CC-PROTECT Thesis Contribution and Future Direction Application Middleware/ OS Hardware Network

36 36 Overall Thesis Contribution Cross-layer methodology to design mobile multimedia embedded systems with minimal costs 1. Effective Cross-layer approaches for reliability 2. Low-cost reliability 3. Expanded trade-off space 4. Extended applicability of existing techniques Application Middleware/ OS Hardware Soft Error Packet Loss Network

37 37 Effectiveness of Thesis Proposals (Energy Saving) PPC 25% energy reduction, as compared to a conventional protected cache with ECC EAVE 30% energy reduction, as compared to a conventional video encoding CCPROTECT 56% energy reduction, as compared to a conventional composition of protections

38 38 Publication Application Middleware / OS Hardware [Lee, ACMMM08] [Mohapatra, IPDPS05] [Lee, ICME05] [Lee, DIPES08] Network [Lee, TVLSI08] [Lee, PPCDIPES08] [Lee, CASES06] [Lee, ACMMM08] K. Lee, A. Shirvastava, M. Kim, N. Dutt, and N. Venk atasubramanian, Mitigating the impact of hardware defects on multimedia applications A cross-layer approach, In ACM Inter national Conference on Multimedia, Oct [Lee, TVLSI08] K. Lee, A. Shrivastava, I. Issenin, N. Dutt, and N. Venkata subramanian, Partially protected caches to reduce failures due t o soft errors in multimedia applications, In IEEE Transactions on V ery Large Scale Integration Systems (TVLSI), 2008, to appear. [Lee, DIPES08] K. Lee, M. Kim, N. Dutt, and N. Venkatasubramanian, E rror exploiting video encoder to extend energy/qos tradeoffs f or mobile embedded systems, In 6th IFIP Working Conference o n Distributed and Parallel Embedded Systems (DIPES), Sep [Lee, PPCDIPES08] K. Lee, A. Shrivastava, N. Dutt, and N. Venkatasubr amanian, Data partitioning techniques for partially protected ca ches to reduce soft error induced failures, In 6th IFIP Working C onference on Distributed and Parallel Embedded Systems (DIPES), Sep [Lee, CASES06] K. Lee, A. Shrivastava, I. Issenin, N. Dutt, and N. Venkat asubramanian, Mitigating soft error failures for multimedia appl ications by selective data protection, In Int. Conference on Compi lers, Architecture, & Synthesis for Embedded Systems (CASES), Oct [Lee, ICME05] K. Lee, N. Dutt, and N. Venkatasubramanian, Experime ntal Study on Energy Consumption of Video Encryption for Mobil e Handheld Devices", In IEEE International Conference on Multime dia and Expo (ICME 05), Poster Session, July [Mohapatra, IPDPS05] S. Mohapatra, R. Cornea, H. Oh, K. Lee, M. Kim, N. Dutt, R. Gupta, A. Nicolau, S. Shukla, and N. Venkatasubramanian, A cross-layer approach for powerperformance optimization in distributed mobile systems, In Next Generation Software Program in conjunction with IEEE International Parallel and Distributed Processing Symposium (IPDPS), April 2005.

39 39 Future Direction Error Rate Translation/Integration Different types of errors Different components across system layers Cross-layer methods for distributed embedded systems (Horizontal Expansion) Network-aware methods Context-aware approaches Exce ption Application Error-prone Networks Mobile Video Application Middleware/ OS Hardware Bug Soft Error Network Packet Loss

40 40 Thank you! Any Questions or Comments?

41 41 Backup Slides

42 42 Why Cross-Layer Approach? Cross-layer interactions and conflicts arise between system properties DVS increases SER exponentially Over protection or under protection All ECC for multimedia data is an overkill Cross-layer approaches can maximize the reliability with minimal power and performance overheads Benefits of Cross-layer approaches Global system view Coordination for intelligent selection Adaptation Cross-layer approaches have been promising to save the resources at the cost of QoS [Mohapatra, 05][Yuan, 04] DVS: Dynamic Voltage Scaling SER: Soft Error Rate ECC: Error Correction Codes QoS: Quality of Service

43 43 Thesis Proposed Contribution: CC-PROTECT Cooperative Cross-layer Protection (CC-PROTECT) by exploiting error-awareness and error control schemes across system abstraction layers Contribution Present cost-efficient reliability methods (cooperative crosslayer protection) Open expanded tradeoff spaces and operating points Rediscover applicability of existing approaches for other purposes

44 44 Performance vs. Capacity Total energy available from a battery is a design issue and is fixed at a design time, along with its weight and size Stark contrast between linear growth rate of battery capacity and exponential technology improvement rate of system components [Udani] Sanjay Udani and Jonathan Smith, Power management in mobile computing

45 [Chetan, SPC04] S. Chetan, A. Ranganathan, and R. Campbell, Towards Fault Tolerant Pervasive Computing, in SPC 04 [Somani, IEEECom97] A. K. Somani and N. H. Vaidya, Understanding Fault Tolerance and Reliability, in IEEE Computer 97 vol. 30 issue 4 45 Generalized Fault Tolerance Techniques 1) Modular Redundancy 2) N-Version Programming 3) Error-Control Coding 4) Checkpoints and Rollbacks 5) Recovery Blocks

46 46 1) Modular Redundancy Modular Redundancy Multiple identical replicas of hardware modules Voter mechanism Compare outputs and select the correct output fault Producer A Producer B voter Data Consumer Tolerate most hardware faults Effective but expensive

47 47 2) N-version Programming N-version Programming Different versions by different teams Different versions may not contain the same bugs Voter mechanism Tolerate some software bugs Program fault i Programmer K Producer A voter Program j Programmer L Data Consumer

48 48 3) Error-Control Coding Error-Control Coding Replication is effective but expensive Error-Detection Coding and Error-Correction Coding (example) Parity Bit, Hamming Code, CRC Much less redundancy than replication Producer A fault Data Error Control Consumer Data

49 49 4) Checkpoints & Rollbacks Checkpoints and Rollbacks Checkpoint A copy of an application s state Save it in storage immune to the failures Rollback Restart the execution from a previously saved checkpoint Recover from transient and permanent hardware and software failures Data Producer A Application State K state (K-1) state K Checkpoint Rollback fault Consumer

50 50 5) Recovery Blocks Recovery Blocks Multiple alternates to perform the same functionality One Primary module and Secondary modules Different approaches 1) Select a module with output satisfying acceptance test 2) Recovery Blocks and Rollbacks Restart the execution from a previously saved checkpoint with secondary module Tolerate software failures Producer A Application Block X Block X2 Block Y Block Z state (K-1) Checkpoint state K fault Data Rollback Consumer

51 51 Soft Errors (Transient Faults) SER increases exponentially as technology scales Integration, voltage scaling, altitude, latitude [Baumann, 05] Caches are most hit due to: Larger portion in processors (more than 50%) No masking effects (e.g., logical masking) Intel Itanium II Processor Transistor 01 Bit Flip 5 hours MTTF 1 month MTTF MTTF: Mean time To Failure

52 52 Related Work Process Technology Solutions Hardening [Baze, IEEE Trans. on Nuclear Science 00] SOI [O. Musseau, IEEE Trans. on Nuclear Science 96] Process complexity, yield loss, and substrate cost Our Solution -Protects caches from failures due to soft errors exploiting error-tolerance of applications -Protection can be in conjunction with any techniques Microarchitectural Solutions for Caches Cache Scrubbing [Mukherjee, PRDC04] Low Power Cache [Li, ISLPED04] Area Efficient Protection [Kim, DATE06] Multiple Bit Correction [Neuberger, TODAES 03] Cache Size Selection [Cai, ASP- DAC06] In-Cache Replication [Zhang, DSN03] Replication Cache [Zhang, IEEE Computers 05] High overheads in terms of power, performance, and area

53 53 Unequal Data Protection All pages are not equally failure critical Multimedia data is failure noncritical Program variables are failure critical Failures: system crash, infinite loop, segmentation faults, etc QoS degradation is not a failure Only 9 pages out of 83 are failure critical

54 54 Failure Critical and Failure Non-Critical Data

55 55 Soft Errors on Increase Increase exponentially due to technology scaling 0.18 µm 1,000 FIT per Mbit of SRAM 0.13 µm 10,000 to 100,000 FIT per Mbit of SRAM Voltage Scaling SER N flux Voltage scaling increases SER significantly x CS x exp {- where Q critical = C V x Q critical Q s }

56 56 Experimental Setup for Page Failure Rates

57 57 Experimental Framework

58 Experimental Results Failure Rate 58 Failure rate of PPC is close to that of Safe (Safe is a protected cache configuration with an ECC protection, i.e., protecting all data, and Unsafe is an unprotected cache)

59 Experimental Results Performance 59 Runtime of PPC is close to that of Unsafe

60 Experimental Results Power 60 Energy consumption of PPC is close to that of Unsafe

61 61 Experimental Setup for DPExplore

62 62 DPExplore Results

63 63 Video Encoding

64 64 Error-Resilient Video Encoding Parameters PLR Resilience Network Error-resilient video encodings have been developed to combat errors in networks PBPAIR energyefficient and errorresilient video encoding [Kim,06] Passive Error Exploitation It compresses video data according to PLR Embed Error-Resilience against packet losses Error-prone Networks Mobile Video Application Packet Loss Maintain the QoS PBPAIR: Probability-Based Power Aware Intra Refresh

65 65 Related Work Energy/QoS-aware video encoding Video encoding parameters [Mopatra, IPDPS05] Motion estimation algorithm [Tourapis, VCIP00] Integrated power management [Mohapatra, ACM MM03] Global cross-layer adaption [Yuan, MMCN04] Transmission power and QoS [Eisenberg, IEEE Trans. on CSVT 02] Not consider error-resilience Error-resilient video encoding Error-resilient GOP [Yang, JVCIP07] AIR (Adaptive Intra Refreshing) [Worral, ICASSP01] PGOP (Progressive GOP) [Cheng, PCS04] PBPAIR (Probability-Based Power Aware Intra Refresh) [Kim, MCCR06] Passive error exploitation Our Solution -Error-aware video encoding: exploits errors actively to minimize energy consumption

66 66 EE-PBPAIR

67 67 Experimental Setup

68 68 Experimental Results Energy Reduction Energy saving occurs at every component in a path from encoding to decoding in mobile video applications EC = Energy Consumption Enc EC = EC for Encoding Tx EC = EC for Transmission Dec EC = EC for Decoding Rx EC = EC for Receiving PLR = 10% and EIR = 10% PSNR: Peak Signal to Noise Ratio

69 69 Experimental Results Expanded Tradeoff Space

70 70 Experimental Energy Saving Source EC = Enc EC + Tx EC Destination EC = Rx EC + Dec EC

71 71 Experimental Results Adaptive EIR Feedbackbased approach (Adaptive EE- PBPAIR) maintains the required video quality compared to Static EE- PBPAIR

72 72 Adaptive EIR

73 73 Conclusion Studied two main crosslayer approaches PPC EAVE Demonstrated the effectiveness of our cooperative cross-layer approaches by exploiting error tolerance and error control schemes EIR feedback Tolerance Unequal Protection FLR Resilience PLR Network

74 74 Failure Rate

75 75 Video Quality

76 76 Memory Access Time (performance)

77 77 Future Direction Cooperative approaches combining PPC and EAVE Middleware-driven cross-layer approach manages error control schemes Translate errors to exploit existing approaches at other abstraction layers PPC EIR Apply our approach for other components feedback Instruction caches and logics EAVE Unequal Intelligent frame dropping techniques Protection To maximize the energy saving while minimizing the quality degradation FLR SER Tolerance Resilience PLR

78 78 Thesis Outline Thesis proposes a cross-layer method Exploit errors and error control schemes across layers to maximize reliability with minimal costs for mobile embedded systems Topic 1 Approach at hardware and application layers PPC (unequal data protection at hardware exploiting error tolerance at application) [Lee, CASES06][Lee, DIPES08][Lee, TVLSI08] Topic 2 Approach at application, middleware, and network layers EAVE (intentional exploitation of errors at application, incorporating error resilience in networks) [Lee, DIPES08] Topic 3 Approach across application/middleware-os/hw Application Middleware/ OS Hardware CC-PROTECT (middleware-driven cooperative exploitation of errors and error control schemes across layers) [Lee, ACM MM 08] Network

79 79 References (cross-layers and tools) [Bajic, 07] I. V. Bajic. Efficient cross-layer error control for wireless video multicast. 53(1): , Mar [Dynamo] DYNAMO. Power Aware Middleware for Distributed Mobile Computing. University of California at Irvine, [Forge] FORGE Project. A Framework for Optimization of Distributed Embedded Systems Software. University of California at Irvine, [Grace] GRACE Project. Global Resource Adaptation through CoopEration. University of Illinois at Urbana-Champaign, [Kim, 08] M. Kim, N. Dutt, N. Venkatasubramanian, and C. Talcott. xtune: Online verifiable cross-layer adaptation for distributed real-time embedded systems. ACM SIGBED Review: Special Issue on the RTSS Forum on Deeply Embedded Real-Time Computing, 5(1), Jan [Mohapatra, 03] S. Mohapatra, R. Cornea, N. Dutt, A. Nicolau, and N. Venkatasubramanian. Integrated power management for video streaming to mobile handheld devices. In ACM international conference on Multimedia, [Mohapatra, 05] S. Mohapatra, R. Cornea, H. Oh, K. Lee, M. Kim, N. Dutt, R. Gupta, A. Nicolau, S. Shukla, and N. Venkatasubramanian. A cross-layer approach for power-performance optimization in distributed mobile systems. In Next Generation Software Program in conjunction with IPDPS, page 218.1, April [Shivakumar, 01] P. Shivakumar and N. Jouppi. CACTI 3.0: An Integrated Cache Timing, Power, and Area Model. In WRL Technical Report 2001/2, [Synopsys] Synopsys Inc., Mountain View, CA, USA. Design Compiler Reference Manual, [Schaar, 07] M. van der Schaar and D. S. Turaga. Cross-layer packetization and retransmission strategies for delay-sensitive wireless multimedia transmission. IEEE Transactions on Multimedia, 9(1): , Jan [Vuran, 06] M. C. Vuran and I. F. Akyildiz. Cross-layer analysis of error control in wireless sensor networks. In IEEE Communications Society on Sensor and Ad Hoc Communications and Networks (SECON), pages , Sep [Yuan, 03] W. Yuan and K. Nahrstedt. Energy-efficient soft real-time CPU scheduling for mobile multimedia systems. 37(5): , Dec [Yuan, 04] W. Yuan and K. Nahrstedt. Practical voltage scaling for mobile multimedia devices. In ACM international conference on Multimedia, pages , 2004.

80 80 References (soft errors and reliability) [Baumann, 05] R. Baumann. Soft errors in advanced computer systems. IEEE Design and Test of Computers, pages , [Hazucha, 00] P. Hazucha and C. Svensson. Impact of CMOS technology scaling on the atmospheric neutron soft error rate. IEEE Trans. on Nuclear Science, 47(6): , [Li, 05] J.-F. Li and Y.-J. Huang. An error detection and correction scheme for RAMs with partial-write function. In IEEE International Workshop on Memory Technology, Design and Testing (MTDT), pages , [Li, 04] L. Li, V. Degalahal, N. Vijaykrishnan, M. Kandemir, and M. J. Irwin. Soft error and energy consumption interactions: A data cache perspective. In ISLPED, Aug [Mastipuram, 04] R. Mastipuram and E. C. Wee. Soft Errors Impact on System Reliability. Sep [Phelan, 03] R. Phelan. Addressing soft errors in arm core-based designs. Technical report, ARM, [Pradhan, 96] D. K. Pradhan. Fault-Tolerant Computer System Design. Prentice Hall, ISBN [Shrivastava, 05] A. Shrivastava, I. Issenin, and N. Dutt. Compilation techniques for energy reduction in horizontally partitioned cache architectures. In CASES, pages 90 96, [Wrobel, 01] F. Wrobel, J. M. Palau, M. C. Calvet, O. Bersillon, and H. Duarte. Simulation of nucleon-induced nuclear reactions in a simplified SRAM structure: Scaling effects on SEU and MBU cross sections. IEEE Trans. on Nuclear Science, 48(6), [Xu, 96] J. Xu and B. Randell. Roll-forward error recovery in embedded real-time systems. In ICPADS, page 414, [Nieuwland, 06] A. K. Nieuwland and S. Jasarevic and G. Jerin. Combinational Logic Soft Error Analysis and Protection. In IOLTS06, 2006.

81 81 References (error-resilient encoding, etc.) [Cheng, 04] L. Cheng and M. E. Zarki. PGOP: An error resilient techniques for low bit rate and low latency video communications. In Picture Coding Symposium (PCS), Dec [Kim, 06] M. Kim, H. Oh, N. Dutt, A. Nicolau, and N. Venkatasubramanian. PBPAIR: An energy-efficient error-resilient encoding using probability based power aware intra refresh. ACM SIGMOBILE Mobile Computing and Communications Review, 10(3):58 69, July [Wang, 98] Y.Wang and Q.-F. Zhu. Error control and concealment for video communication: A review. 86(5): , May [Worrall, 01] S. Worrall, A. Sadka, P. Sweeney, and A. Kondoz. Motion adaptive error resilient encoding for MPEG-4. In ICASSP, May 2001.