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ÇѱÛÁ¦¸ñ(Korean Title) °í¼º´É GPUÀÇ ¼º´É ÀúÇÏ ¿äÀο¡ ´ëÇÑ Á¤·®Àû ºÐ¼®
¿µ¹®Á¦¸ñ(English Title) Quantitative Analysis of the Negative Factors on the GPU Performance
ÀúÀÚ(Author) ÃÖÈ«ÁØ   ÀüÇü±Ô   ±èöȫ   HongJun Choi   HyungGyu Jeon   Cheolhong Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 18 NO. 04 PP. 0282 ~ 0287 (2012. 04)
Çѱ۳»¿ë
(Korean Abstract)
ÃÖ±Ù, GPU ¼º´ÉÀÌ ±Þ¼Óµµ·Î Çâ»óµÇ¸é¼­ CPU¸¦ ´ëüÇÒ ¼ö Àִ ó¸®±â·Î¼­ÀÇ GPU¿¡ ´ëÇÑ °ü½ÉÀÌ ´õ¿í ³ô¾ÆÁö°í ÀÖ´Ù. GPUÀÇ ¼º´ÉÀº ÇöÀç±îÁö´Â ºñ¾àÀûÀ¸·Î Çâ»óµÇ¾î ¿ÔÁö¸¸, ÇâÈÄ¿¡µµ Áö¼ÓÀûÀÎ ¼º´É Çâ»óÀ» ±â´ëÇϱâ À§Çؼ­´Â GPUÀÇ ¼º´É¿¡ ºÎÁ¤ÀûÀÎ ¿µÇâÀ» ÁÖ°í ÀÖ´Â ¿äÀε鿡 ´ëÇÑ »ó¼¼ÇÑ ºÐ¼®ÀÌ ¼ö¹ÝµÇ¾î¾ß ÇÑ´Ù. À̸¦ À§ÇØ, º» ³í¹®¿¡¼­´Â °í¼º´É »ó¿ë GPUÀÇ ¼º´É¿¡ ºÎÁ¤ÀûÀÎ ¿µÇâÀ» ¹ÌÄ¡´Â ¿äÀεéÀ» Å©°Ô 5°¡Áö·Î ºÐ·ùÇÏ°í, °¢°¢ÀÇ ¿äÀεéÀÌ ¼º´É¿¡ ¹ÌÄ¡´Â ¿µÇâÀ» Á¤·®ÀûÀ¸·Î ºÐ¼®ÇÏ°íÀÚ ÇÑ´Ù. ½ÇÇè °á°ú¿¡ ÀÇÇϸé, ´ë¿ë·® µ¥ÀÌÅÍ Ã³¸® ÀÀ¿ëÇÁ·Î±×·¥À» GPU¿¡¼­ ¼öÇàÇÏ´Â °æ¿ì¿¡´Â ¸Þ¸ð¸® ¿À¹öÇìµå·Î ÀÎÇØ ¼º´ÉÀÌ ÃÖ´ë 12.6% ÀúÇϵȴÙ. ¿¬»ê ÁýÁß ÀÀ¿ëÇÁ·Î±×·¥À» ¼öÇàÇÏ´Â °æ¿ì¿¡´Â ³»ºÎ¿¬°á¸Á Áö¿¬°ú ·¹Áö½ºÅÍ ÆÄÀÏ Ãæµ¹ ¶§¹®¿¡ ¹ß»ýÇÏ´Â ¿À¹öÇìµå·Î ÀÎÇØ 3.5%ÀÇ ¼º´ÉÀÌ ÀúÇϵÊÀ» ¾Ë ¼ö ÀÖ´Ù.
¿µ¹®³»¿ë
(English Abstract)
The performance of Graphic Processing Unit (GPU) has been improved dramatically. To improve the GPU performance continuously, a quantitative analysis on the various factors which degrade the GPU performance should be provided. In this paper, we divide the negative factors on the GPU performance into five types and analyze the impact of each factor quantitatively. According to our experimental results using GPGPU-SIM, memory overhead degrades the GPU performance by 12.6% when the mass-data applications are executed. In cases that computation-intensive applications are executed, the degradation of GPU performance caused by the interconnection overhead and register file overhead is measured as 3.5%.
Å°¿öµå(Keyword) ±×·¡ÇÈó¸®ÀåÄ¡   °í¼º´É   ¸Þ¸ð¸® ¿ä±¸ Áö¿¬   ³»ºÎ¿¬°á¸Á Áö¿¬   ·¹Áö½ºÅÍ ÆÄÀÏ Áö¿¬   GPU   High performance   Memory overhead   Interconnection overhead   Register file overhead  
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