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博碩士論文 etd-0707114-134411 詳細資訊
Title page for etd-0707114-134411
論文名稱
Title
應用於三維繪圖處理器之低功率指令模式調整系統
Low-power Instruction Mode Adjustment for 3-D Graphics Processing Unit
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
66
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2014-07-24
繳交日期
Date of Submission
2014-08-07
關鍵字
Keywords
指令模式調整系統、三維繪圖處理器、多重精確度模式算術處理單元、低功率設計
3-D Graphics Processing Unit, Multi-precision Arithmetic Units, Low-power Design, Instruction Mode Adjustment
統計
Statistics
本論文已被瀏覽 5645 次,被下載 70
The thesis/dissertation has been browsed 5645 times, has been downloaded 70 times.
中文摘要
隨著電子產品快速地推陳出新,可攜式電子產品已成為3C時代之主流發展趨勢。為了滿足三維影像高畫質輸出品質需求並且提升三維圖形計算的執行效率,許多可攜式電子產品已採用三維圖形處理器。然而,執行三維圖形處理將會消耗大量的電力,對於依賴電池供電的可攜式電子產品而言,將導致快速降低電池的使用時間。因此,在設計可攜式電子產品的過程中,如何延長電池續航力是最重要的考量之一。直到現在,有效延長電池續航力的最佳方法之一,即是在三維圖形處理器上發展低功率設計。由於人眼先天視覺的限制,對於輕微失真的三維影像無法快速分辨。換句話說,我們可以犧牲指令些許的精準度,換取功率消耗的降低。為了達成這個目標,本論文針對三維圖形處理器提出一個低功率指令模式調整系統,首先將三維圖形處理器的單精度浮點數算術運算單元,替換成多重精確度模式的運算處理單元,接著發展一套快速指定指令精確度模式的調整方法,根據使用者設定的誤差限制,指定乘加運算與特殊運算指令的精確度模式,藉由損失可接受的輸出影像品質,大大地降低功率消耗。
Abstract
With the rapid development of electronic products, portable electronic products have become the mainstream trend of 3C age. To satisfy high output quality of 3-D image and improve the execution efficiency of 3-D calculations, many portable electronic products have adopted 3-D graphic processing units (3-D GPU). However, the large power dissipation of 3-D GPU will cause the portable electronic products, which rely on battery power, to reduce their battery life quickly. Therefore, how to extend the battery life is one of the most important considerations of designing portable electronic products. Until now, the most effective way to extend the battery life is developing the low-power design technique for the 3-D GPU. Owing to the congenital visual limitation of the human eyes, it is difficult for human to quickly differentiate the insignificant distortions of 3-D image. In other words, we can sacrifice a slight accuracy of instructions for reducing the power consumption. To achieve this object, this thesis proposes a low-power instruction mode adjustment system for 3-D GPU. We first replace the single-precision floating-point arithmetic units of 3-D GPU by multi-precision mode arithmetic units, and then develop a fast instruction precision mode adjustment method which can assign the precision modes to multiply-add and special function operations according to the user-defined error constraints. In the case of output image with the acceptable quality loss, we can reduce the power dissipation significantly.
目次 Table of Contents
論文審定書 i
摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 viii
第一章 緒論 1
1.1 研究動機 1
1.2 論文大綱 3
第二章 研究背景 4
2.1 三維繪圖簡介 4
2.1.1 三維繪圖管線流程 (3D Rendering Pipeline) 4
2.1.2 圖學API簡介 6
2.2 ATTILA模擬器 8
2.2.1 模擬器架構 8
2.2.2 驗證流程 12
2.3 多重精確度算術處理單元 13
2.3.1 多重模式浮點乘加器 13
2.3.2 多重精確度函數插補器 17
第三章 指令模式調整系統 19
3.1 資料非循環圖 21
3.2 仿射算術誤差模型 23
3.3 禁忌搜尋演算法 26
3.4 固定模式指定方法 29
第四章 研究方法與成果 31
4.1 實驗方法 31
4.2 實驗數據與結果 34
第五章 結論與未來研究方向 54
5.1 結論 54
5.2 未來研究方向 55
參考文獻 56
參考文獻 References
[1] J. Pool, A. Lastra, and M. Singh, “Energy-Precision Tradeoffs in Mobile Graphics Processing Units,” IEEE International Conference on Computer Design, pp. 60-67, 2008.
[2] P.H. Wang, Y.M. Chen, and C.L. Yang, “A Predictive Shutdown Technique for GPU Shader Processors,” IEEE Computer Architecture Letters, Vol. 8, No. 1, pp. 9-12, January 2009.
[3] S.L. Chu, C.C. Hsiao, and C.Y. Chen, “A Dual-Mode Unified Shader with Frame-based Dynamic Precision Adjustment for Mobile GPUs,” IFIP Ninth International Conference on Embedded and Ubiquitous Computing, pp. 158-165, 2011.
[4] Khronos Group: http://www.khronos.org/
[5] ATTILA: http://attila.ac.upc.edu/wiki/index.php/Main_Page
[6] Victor Moya del Barrio, Carlos González, Jordi Roca, Agustín Fernández, and Roger Espasa, “ATTILA: A Cycle-Level Execution-Driven Simulator for Modern GPU Architectures,” IEEE International Symposium on Performance Analysis of Systems and Software, pp. 231-241, March 2006.
[7] ARB Vertex Program Extension:
http://oss.sgi.com/projects/ogl-sample/registry/ARB/vertex_program.txt
[8] ARB Fragment Program Extension:
http://oss.sgi.com/projects/ogl-sample/registry/ARB/fragment_program.txt
[9] E. Hokenek, R. Montoye, and P. W. Cook, “Second-Generation RISC Floating Point with Multiply-Add Fused,” IEEE Journal of Solid-State Circuits, Vol. 25, No. 5, pp. 1207-1213, October 1990.
[10] 余其坤,“適用於低功率應用的多重模式浮點乘加器,”國立中山大學, 碩士論文, July 2011.
[11] R. E. Ladner and M. J. Fischer, “Parallel Prefix Computation,” Journal of Association for Computing Machinery(ACM), Vol. 27, No. 4, pp. 831-838, October 1980.
[12] 程建綱, “適用於多媒體應用的多重精確度函數插補器,” 國立中山大學, 碩士論文, July 2012.
[13] J.A. Pineiro, S.F. Oberman, J.-M. Muller and J.D. Bruguera, “High-speed function approximation using a minimax quadratic interpolator,” IEEE Transactions on Computers, Vol. 54, No. 3, pp. 304-318, 2005.
[14] R.C.T Lee, S.S. Tseng, R.C. Chang and Y.T. Tsai, “Introduction to the Design and Analysis of Algorithm(A Strategic Approach),” McGraw Hill, 2005
[15] 吳坤益, “用於降低多重模式浮點數運算單元能量之指令精確度指定方法,” 國立中山大學, 博士論文, July 2014
[16] J.L.D. Comba and J. Stolfi, “Affine arithmetic and its applications to computer graph,” In Proceedings of the VI SIBGRAPI (Brazilian Symposium on Computer Graphics and Image Processing), pp. 9-18, 1993.
[17] James, T., Rego, C., Glover, F., “Multistart Tabu Search and Diversification Strategies for the Quadratic Assignment Problem,” IEEE Transaction on System, Man and Cybernetic, Part A: Systems and Humans, Vol. 39, No.3, pp. 579-596, 2009
[18] Yusra A. Y. Al-Najjar, and Dr. Der Chen Soong, “Comparison of Image Quality Assessment: PSNR, HVS, SSIM, UIQI,” International Journal of Scientific & Engineering Research, Vol. 3, No. 8, August 2012.
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