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Extra resources for Advanced Memory Optimization Techniques for Low Power Embedded Processors
The rest of the chapter is organized as follows: The following section provides an introduction to the non-overlayed scratchpad allocation approaches, which is followed by the presentation of a motivating example. 3 surveys the wealth of work related to non-overlayed scratchpad allocation approaches. 4, preliminaries are described and based on that the scratchpad allocation problems are formally defined. 5 presents the approaches for non-overlayed scratchpad allocation. 6. 7 concludes the chapter with a short summary.
In order to obtain the answer to the above question, we compiled the Edge Detection application for an ARM7 processor using an energy optimizing research compiler (ENCC) . 2. 2 presents the workflow of the Edge Detection application which determines edges in a tomographic image. 1. The left side and the right side of the table present the profile information for functions and arrays of the application, respectively. The execution count for a function is the sum of the execution counts of every instruction in the function, whereas the access count for an array is the sum of the access counts of each array element.
Gauss Blur Compute Edges gb_image in_image Detect Roots out_image ce_image Fig. 2. 1. 2 Motivation We begin by deciding which fragments of the application should be considered as memory objects or as candidates for allocation on the scratchpad memory. Should the set of memory objects consist of only data elements or only instructions, or a combination of both? In order to obtain the answer to the above question, we compiled the Edge Detection application for an ARM7 processor using an energy optimizing research compiler (ENCC) .