abstract: Advances in electronics technology and innovative manufacturing processes have driven the semiconductor industry towards extensive miniaturization & ever greater integration of chip design. One consequence of this sustained evolution has been the growing relative cost of accessing off-chip components with external memory being one of the dominant contributors. In embedded systems and applications, where power consumption and cost are extremely crucial factors, the use of on chip Scratch Pad Memories (SPMs) has proven to be a good alternative to caches. SPMs are more efficient than on-chip caches in a wide variety of aspects including energy consumption, power dissipation, speed performance, area, and timing predictability. However, at the same time, they entail explicit software-level management. Specifically, the system performance depends upon overlay scheme for mapping code and data onto the size-limited SPMs. It has been found that for applications with large code sizes, the overlay overhead cost becomes significant. This work aims to evaluate and implement pre-fetching as a performance improvement technique for SPMs. It is implemented in code overlay manager, provided with the Cell Broadband Engine (CBE) Synergistic Processing Unit (SPU) compiler from IBM, spu-gcc. Four different approaches proposed in this work use profiling information to predict pre-fetch calls. The pre-fetching technique achieves considerable performance improvement by hiding some of the code overlay cost behind active computations by fetching the required code segment in advance into SPM. Experimental results supporting this claim are obtained using the IBM Cell architecture platform with substantial gain of more than 30%. / Dissertation/Thesis / M.S. Computer Science 2011
Identifer | oai:union.ndltd.org:asu.edu/item:8876 |
Date | January 2011 |
Contributors | Ghadge, Nikhil Dadasaheb (Author), Chatha, Dr. Karamvir (Advisor), Shrivastava, Dr. Aviral (Committee member), Lee, Dr. Yann-Hang (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Masters Thesis |
Format | 69 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
Page generated in 0.0022 seconds