Advanced Memory Optimization Techniques for Low-Power Embedded Processors [electronic resource] / by Manish Verma, Peter Marwedel.

By: Verma, Manish [author.]Contributor(s): Marwedel, Peter [author.] | SpringerLink (Online service)Material type: TextTextLanguage: English Publisher: Dordrecht : Springer Netherlands, 2007Description: XII, 188 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781402058974Subject(s): Engineering | Memory management (Computer science) | Software engineering | Computer system performance | Computer science | Systems engineering | Engineering | Circuits and Systems | Programming Languages, Compilers, Interpreters | Memory Structures | Special Purpose and Application-Based Systems | System Performance and EvaluationAdditional physical formats: Printed edition:: No titleDDC classification: 621.3815 LOC classification: TK7888.4Online resources: Click here to access online
Contents:
Related Work -- Memory Aware Compilation and Simulation Framework -- Non-Overlayed Scratchpad Allocation Approaches for Main/Scratchpad Memory Hierarchy -- Non-Overlayed Scratchpad Allocation Approaches for Main/Scratchpad + Cache Memory Hierarchy -- Scratchpad Overlay Approaches for Main/Scratchpad Memory Hierarchy -- Data Partitioning and Loop Nest Splitting -- Scratchpad Sharing Strategies for Multiprocess Applications -- Conclusions and Future Directions.
In: Springer eBooksSummary: The design of embedded systems warrants a new perspective because of the following two reasons: Firstly, slow and energy inefficient memory hierarchies have already become the bottleneck of the embedded systems. It is documented in the literature as the memory wall problem. Secondly, the software running on the contemporary embedded devices is becoming increasingly complex. It is also well understood that no silver bullet exists to solve the memory wall problem. Therefore, this book explores a collaborative approach by proposing novel memory hierarchies and software optimization techniques for the optimal utilization of these memory hierarchies. Linking memory architecture design with memory-architecture aware compilation results in fast, energy-efficient and timing predictable memory accesses. The evaluation of the optimization techniques using real-life benchmarks for a single processor system, a multiprocessor system-on-chip (SoC) and for a digital signal processor system, reports significant reductions in the energy consumption and performance improvement of these systems. The book presents a wide range of optimizations, progressively increasing in the complexity of analysis and of memory hierarchies. The final chapter covers optimization techniques for applications consisting of multiple processes found in most modern embedded devices. Advanced Memory Optimization Techniques for Low Power Embedded Processors is designed for researchers, complier writers and embedded system designers / architects who wish to optimize the energy and performance characteristics of the memory subsystem.
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Related Work -- Memory Aware Compilation and Simulation Framework -- Non-Overlayed Scratchpad Allocation Approaches for Main/Scratchpad Memory Hierarchy -- Non-Overlayed Scratchpad Allocation Approaches for Main/Scratchpad + Cache Memory Hierarchy -- Scratchpad Overlay Approaches for Main/Scratchpad Memory Hierarchy -- Data Partitioning and Loop Nest Splitting -- Scratchpad Sharing Strategies for Multiprocess Applications -- Conclusions and Future Directions.

The design of embedded systems warrants a new perspective because of the following two reasons: Firstly, slow and energy inefficient memory hierarchies have already become the bottleneck of the embedded systems. It is documented in the literature as the memory wall problem. Secondly, the software running on the contemporary embedded devices is becoming increasingly complex. It is also well understood that no silver bullet exists to solve the memory wall problem. Therefore, this book explores a collaborative approach by proposing novel memory hierarchies and software optimization techniques for the optimal utilization of these memory hierarchies. Linking memory architecture design with memory-architecture aware compilation results in fast, energy-efficient and timing predictable memory accesses. The evaluation of the optimization techniques using real-life benchmarks for a single processor system, a multiprocessor system-on-chip (SoC) and for a digital signal processor system, reports significant reductions in the energy consumption and performance improvement of these systems. The book presents a wide range of optimizations, progressively increasing in the complexity of analysis and of memory hierarchies. The final chapter covers optimization techniques for applications consisting of multiple processes found in most modern embedded devices. Advanced Memory Optimization Techniques for Low Power Embedded Processors is designed for researchers, complier writers and embedded system designers / architects who wish to optimize the energy and performance characteristics of the memory subsystem.

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