【文章內(nèi)容簡介】 has been the only viable alternative for large scale technical scientific puting for several years, as we observe in the evolution of the TOP500 systems.) In this paper, we study the behavior of an emerging mercial application, search of unstructured data, in two distinct systems: One is a modern scaleup system based on the POWER5 multicore/multithreaded processor [8],[9]. The other is a typical scaleout system based on IBM BladeCenter [3]. The systems were configured to have approximately the same list price (approximately $200,000), allowing a fair performance and priceperformance parison. One of the more important conclusions of our work is that a “pure” scaleup approach is not very effective in using all the processors in a large SMP. In pure scaleup, we run just one instance of our application in the SMP, and that instance uses all the resources (processors) available. We were more successful in exploiting the POWER5 SMP with a “scaleoutinabox” approach. In that case, multiple instances of the application run concurrently, within a single operating system. This latter approach resulted in significant gains in performance while maintaining the single system image that is one of the great advantages of large SMPs. Another conclusion of our work is that a scaleout system can achieve about four times the performance of a similarly priced scaleup system. In the case of our application, this performance is measured in terms of queries per second. The scaleout system requires the use of multiple system images, so the gain in performance es at a convenience and management cost. Depending on the situation, that may be worth the improvement in performance or not. The rest of this paper is organized as 2 describes the configuration of the scaleout and scaleup systems we used in our study. Section 3 presents the Nutch/Lucene workload that ran in our systems. Section 4 reports our experimental , Section 5 presents our conclusions. 2 Scaleup and scaleout systems In the IBM product line, Systems z, p, and i are allbased on SMPs of different sizes that span a widespectrum of putational capabilities. As an example of a stateofthe art scaleup system we adopted the POWER5 p5 575 machine [7]. This 8 or 16way system has been very attractive to customers due to its lowcost, highperformance and small form factor (2U or high in a 24inch rack). A picture of a POWER5 p5 575 is shown in Figure 1. generally consist of multiple interconnected nodes with a selfcontained operating system in each node. We chose BladeCenter as our platform for scaleout. This was a natural choice given the scaleout orientation of this platform. The first form of scaleout systems to bee popular in mercial puting was the rackmounted cluster. The IBM BladeCenter, solution (and similar systems from panies such as HP and Dell) represents the next step after rackmounted clusters in scaleout systems for mercial puting. The blade servers used in BladeCenter are similar in capability to the densest rackmounted cluster servers: 4processor configurations, 1632 GiB of maximum memory, builtin Ether, and expansion cards for either Fiber Channel, Infiniband, Myri, or 10 Gbit/s Ether. Also offered are doublewide blades with up to 8processor configurations and additional memory. Figure 2 is a highlevel view of our cluster architecture. The basic building block of the cluster The particular p5 575 that we used for our scaleup measurements has 16 POWER5 processors in 8 dualcore modules and 32 GiB (1 GiB = 1,07 3 ,741,824bytes) of main memory. Each co