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Energy-Aware Parameter Passing 511 the same way. However, each access to a formal parameter invokes a fresh computation of the value of the actual parameter. Conservative: In this strategy, the multiple uses problem is resolved as in the case of the Block Insertion strategy. However, if the global variable problem occurs, this strategy drops on-demand parameter-passing and uses the original parameter-passing strategy. Closure: This is similar to the previous strategy except that in handling the global variable problem, it uses the closure-based mechanism discussed earlier in Section 3. It should be mentioned that this strategy passes a parameter as the first (default) strategy if the global variable problem does not occur. We observe from Figure 36-4 that the default on-demand strategy improves energy consumption by 8.78%, on the average. It is most successful in applications Wood and Encr where there is a relatively large difference between the average number of parameters and the average number of active parameters. The Path Control and Multiple Evaluation strategies, on the other hand, achieve less saving in energy. In fact, in two applications, Atr and SP, evaluating the same actual parameter more than once results in energy loss (as compared to the case without on-demand parameter-passing). The reason that it is relatively successful in remaining applications is the fact that in many subroutine executions the paths where multiple actual parameter evaluations occur are not taken at runtime. The reason that the Path Control strategy is not as successful as the Block Insertion strategy is the extra energy spent in maintaining the values of the path variables and in executing comparison operations. The percentage (average) improvements due to Path Control and Multiple Evaluation strategies are 6.68% and 2.98%, respectively. Conservative and Closure generate the same energy behavior as the default strategy in our three applications. This is because in these applications, the global variable problem does not occur. In Usonic and Wood, on the other hand, the default strategy outperforms Conservative and Closure. The trends in Figure 36-5 are similar to those illustrated in Figure 36-4. This is not surprising as eliminating redundant computation saves both energy and execution cycles. It should be stressed, however, that the savings in execution cycles are lower than those in energy consumption. This is due to the fact that the processor we consider can execute multiple instructions in the same cycle; consequently, some of the redundant computation can be hidden (which makes the base case – without on-demand parameter-passing – appear stronger). However, unlike execution cycles, it is not possible to hide energy consumption. 5. CONCLUSIONS In this work, we studied the possibility of modifying the parameter-passing mechanism of the language with some help from compiler. Using a set of
512 Chapter 36 five real-life applications and a custom simulator, we investigated the energy and performance impact of an on-demand parameter-passing strategy. In this strategy, the value of an actual parameter is not computed if the corresponding formal parameter is not used within the subroutine. Our experiments show that one implementation of on-demand parameter-passing results in energy savings ranging from 4.42% to 14.11%, averaging in 8.78%. REFERENCES 1. 2. 3. 4. 5. 6. A. V. Aho, R. Sethi, and J. D. Ullman. Compilers: Principles, Techniques, and Tools, Addison-Wesley Publishing Company, 1986. S. P. Amarasinghe, J. M. Anderson, M. S. Lam, and A. W. Lim. “An Overview of a Compiler for Scalable Parallel Machines.” In Proceedings of the 6th Workshop on Languages and Compilers for Parallel Computing, August, 1993. E.-Y. Chung, L. Benini, and D. De Micheli. “Energy-Efficient Source Code Transformation Based on Value Profiling.” In Proceedings of the 1st Workshop on Compilers and Operating Systems for Low Power, Philadelphia, PA, 2000. M. Kamble and K. Ghose. “Analytical Energy Dissipation Models for Low Power Caches.” In Proceedings of the International Symposium on Low Power Electronics and Design, p. 143, August 1997. R. W. Sebesta. Concepts of Programming Languages, Addison-Wesley Publishing, 2001. N. Vijaykrishnan, M. Kandemir, M. J. Irwin, H. Y. Kim, and W. Ye. “Energy-Driven Integrated Hardware-Software Optimizations Using SimplePower.” In Proceedings of The International Symposium on Computer Architecture, June 2000.
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EMBEDDED SOFTWARE FOR SoC
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Embedded Software for SoC Edited by
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DEDICATION This book is dedicated t
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TABLE OF CONTENTS Dedication Conten
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Table of Conents Chapter 16 EMBEDDE
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Table of Conents Chapter 33 ADAPTIV
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PREFACE The evolution of electronic
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INTRODUCTION Embedded software is b
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Introduction xvii software consists
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Introduction xix Energy-aware techn
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PART I: EMBEDDED OPERATING SYSTEMS
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Chapter 1 APPLICATION MAPPING TO A
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Application Mapping to a Hardware P
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Chapter 2 FORMAL METHODS FOR INTEGR
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Formal Methods for Integration of A
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Chapter 3 LIGHTWEIGHT IMPLEMENTATIO
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Lightweight Implementation of the P
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Chapter 4 DETECTING SOFT ERRORS BY
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Detecting Soft Errors by a Purely S
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PART II: OPERATING SYSTEM ABSTRACTI
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Chapter 5 RTOS MODELING FOR SYSTEM
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RTOS Modeling for System Level Desi
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Chapter 6 MODELING AND INTEGRATION
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Modeling and Integration of Periphe
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Chapter 7 SYSTEMATIC EMBEDDED SOFTW
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Systematic Embedded Software Genera
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PART III: EMBEDDED SOFTWARE DESIGN
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Chapter 8 EXPLORING SW PERFORMANCE
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Exploring SW Performance 99 of late
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Exploring SW Performance 101 operat
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Exploring SW Performance 103 The ch
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Exploring SW Performance 105 2.2. T
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Exploring SW Performance 107 Figure
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Exploring SW Performance 109 modem
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Chapter 9 A FLEXIBLE OBJECT-ORIENTE
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A Flexible Object-Oriented Software
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Chapter 10 SCHEDULING AND TIMING AN
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Analysis of HW/SW On-Chip Communica
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Chapter 11 EVALUATION OF APPLYING S
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Evaluation of Applying SpecC to the
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Chapter 12 INTERACTIVE RAY TRACING
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Interactive Ray Tracing on Reconfig
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Chapter 13 PORTING A NETWORK CRYPTO
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Porting a Network Cryptographic Ser
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PART IV: EMBEDDED OPERATING SYSTEMS
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Chapter 14 INTRODUCTION TO HARDWARE
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Introduction to Hardware Abstractio
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Chapter 15 HARDWARE/SOFTWARE PARTIT
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Hardware and Software Partitioning
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Chapter 16 EMBEDDED SW IN DIGITAL A
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Embedded SW in Digital AM-FM Chipse
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Embedded SW in Digital AM-FM Chipse
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PART V: SOFTWARE OPTIMISATION FOR E
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Chapter 17 CONTROL FLOW DRIVEN SPLI
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Control Flow Driven Splitting of Lo
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Chapter 18 DATA SPACE ORIENTED SCHE
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Data Space Oriented Scheduling 233
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Chapter 19 COMPILER-DIRECTED ILP EX
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Compiler-Directed ILP Extraction 24
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Chapter 20 STATE SPACE COMPRESSION
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State Space Compression in History
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Chapter 21 SIMULATION TRACE VERIFIC
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Simulation Trace Verification for Q
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PART VI: ENERGY AWARE SOFTWARE TECH
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Chapter 22 EFFICIENT POWER/PERFORMA
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Efficient Power/Performance Analysi
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Chapter 23 DYNAMIC PARALLELIZATION
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Dynamic Parallelization of Array 30
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Chapter 24 SDRAM-ENERGY-AWARE MEMOR
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SDRAM-Energy-Aware Memory Allocatio
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PART VII: SAFE AUTOMOTIVE SOFTWARE
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Chapter 25 SAFE AUTOMOTIVE SOFTWARE
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Safe Automotive Software Developmen
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PART VIII: EMBEDDED SYSTEM ARCHITEC
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Chapter 26 EXPLORING HIGH BANDWIDTH
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Exploring High Bandwidth Pipelined
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Chapter 27 ENHANCING SPEEDUP IN NET
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Enhancing Speedup in Network Proces
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Chapter 28 ON-CHIP STOCHASTIC COMMU
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Chapter 29 HARDWARE/SOFTWARE TECHNI
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HW/SW are Techniques for Improving
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Chapter 30 RAPID CONFIGURATION & IN
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Rapid Configuration & Instruction S
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PART IX: TRANSFORMATIONS FOR REAL-T
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Chapter 31 GENERALIZED DATA TRANSFO
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Chapter 32 SOFTWARE STREAMING VIA B
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Software Streaming Via Block Stream
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Chapter 33 ADAPTIVE CHECKPOINTING W
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Adaptive Checkpointing with Dynamic
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