{"title":"探索通用应用程序的图形处理器性能","authors":"P. Trancoso, Maria Charalambous","doi":"10.1109/DSD.2005.40","DOIUrl":null,"url":null,"abstract":"Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications. In this work we present a comprehensive study of the performance of an application executing on the GPU. In addition, we analyze the possibility of using the graphics card to extend the life-time of a computer system. In our experiments we compare the execution on a mid-class GPU (NVIDIA GeForce FX 5700LE) with a high-end CPU (Pentium 4 3.2 GHz). The results show that to achieve high speedup with the GPU you need to: (1) format the vectors into two-dimensional arrays; (2) process large data arrays; and (3) perform a considerable amount of operations per data element. Finally, we study the performance when upgrading a low-end system by simply adding a GPU. This solution is cheaper, results in smaller power consumption and achieves higher speedup (8.1x versus 1.3x) than a full upgrade to a new high-end system.","PeriodicalId":119054,"journal":{"name":"8th Euromicro Conference on Digital System Design (DSD'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":"{\"title\":\"Exploring graphics processor performance for general purpose applications\",\"authors\":\"P. Trancoso, Maria Charalambous\",\"doi\":\"10.1109/DSD.2005.40\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications. In this work we present a comprehensive study of the performance of an application executing on the GPU. In addition, we analyze the possibility of using the graphics card to extend the life-time of a computer system. In our experiments we compare the execution on a mid-class GPU (NVIDIA GeForce FX 5700LE) with a high-end CPU (Pentium 4 3.2 GHz). The results show that to achieve high speedup with the GPU you need to: (1) format the vectors into two-dimensional arrays; (2) process large data arrays; and (3) perform a considerable amount of operations per data element. Finally, we study the performance when upgrading a low-end system by simply adding a GPU. This solution is cheaper, results in smaller power consumption and achieves higher speedup (8.1x versus 1.3x) than a full upgrade to a new high-end system.\",\"PeriodicalId\":119054,\"journal\":{\"name\":\"8th Euromicro Conference on Digital System Design (DSD'05)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"39\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"8th Euromicro Conference on Digital System Design (DSD'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSD.2005.40\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"8th Euromicro Conference on Digital System Design (DSD'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSD.2005.40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 39
摘要
图形处理器被设计成每秒执行多次浮点运算。因此,它们是一种具有吸引力的低成本高性能计算体系结构。然而,如何利用它们在通用应用程序中的所有潜力仍然不是很清楚。在这项工作中,我们对GPU上执行的应用程序的性能进行了全面的研究。此外,我们还分析了使用显卡延长计算机系统寿命的可能性。在我们的实验中,我们比较了中档GPU (NVIDIA GeForce FX 5700LE)和高端CPU (Pentium 4 3.2 GHz)的执行情况。结果表明,要在GPU上实现高加速,需要:(1)将矢量格式化为二维数组;(2)处理大数据阵列;(3)对每个数据元素执行相当多的操作。最后,我们研究了简单增加GPU升级低端系统时的性能。与完全升级到新的高端系统相比,该解决方案更便宜,功耗更小,并且实现了更高的加速(8.1倍对1.3倍)。
Exploring graphics processor performance for general purpose applications
Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications. In this work we present a comprehensive study of the performance of an application executing on the GPU. In addition, we analyze the possibility of using the graphics card to extend the life-time of a computer system. In our experiments we compare the execution on a mid-class GPU (NVIDIA GeForce FX 5700LE) with a high-end CPU (Pentium 4 3.2 GHz). The results show that to achieve high speedup with the GPU you need to: (1) format the vectors into two-dimensional arrays; (2) process large data arrays; and (3) perform a considerable amount of operations per data element. Finally, we study the performance when upgrading a low-end system by simply adding a GPU. This solution is cheaper, results in smaller power consumption and achieves higher speedup (8.1x versus 1.3x) than a full upgrade to a new high-end system.