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Generalized Data Transformations 425 that the reference exhibits spatial reuse in the j loop. Since this loop (j loop) is the innermost loop, we can expect that this reuse will be converted into locality during execution. However, this would not be the case if i was the inner loop and j was the outer loop. Consider the application of a non-singular linear loop transformation to an n-deep loop nest that accesses an array with the subscript function represented as This transformation can be represented by an n × n non-singular transformation matrix T, and maps the iteration of the original loop nest to the iteration of the transformed loop nest [7]. On applying such a transformation, the new subscript function is obtained as that is, the new (transformed) reference matrix is The loop transformation also affects the loop bounds of the iteration space that can be computed using techniques such as Fourier-Motzkin elimination [7]. For convenience, we denote by Q. For example, a loop transformation such as: transforms an original loop iteration to 3. GENERALIZED DATA TRANSFORMATIONS Given an array reference to an m-dimensional array A in an n-level nested loop, a data transformation transforms this reference to Here, corresponds to the transformed array, and and denote the transformed reference matrix and constant vector, respectively. In general, can have dimensions, where Formally, we can define a data transformation for an array A using a pair This pair (referred to as data transformation henceforth) performs the following two mappings: In other words, the original reference matrix X is transformed to and the original constant vector is transformed to We refer to as the data transformation matrix and as the displacement vector. If is the original reference and is the transformed reference, we have and Note that is and has entries. An example data transformation is depicted in Figure 31-4(a). In this data transformation, a 4 × 4 array (for illustrative purposes) is transposed; that is, the array element in the original array is mapped to array element in the transformed space. Note that in this case we have: and
426 Chapter 31 3.1. Motivation In many previous compiler-based studies that employ data transformations for improving cache behavior (e.g., [5]), only the cases where are considered. This is because many of these studies target at reducing capacity misses, rather than conflict misses, and, focusing on each array individually is sufficient for reducing capacity misses in most cases. However, such an approach may not be very effective with conflict misses. Consider, for example, the following loop nest: for (i=0;i
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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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Software Architectural Transformati
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Chapter 35 DYNAMIC FUNCTIONAL UNIT
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Dynamic Functional Unit Assignment
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Chapter 36 ENERGY-AWARE PARAMETER P
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Energy-Aware Parameter Passing 501
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Chapter 37 LOW ENERGY ASSOCIATIVE D
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Low Energy Associative Data Caches
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INDEX abstract communication access
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Index 529 packet flows parameter pa
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Embedded Software for SoC - Grupo de MecatrÃ´nica EESC/USP

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