Architecture and grid application of cluster computing system

Transcription

1 Architecture and grid application of cluter computing ytem Yi Lv*, Shuiqin Yu, Youju Mao Intitute of Optical Fiber Telecom, Chongqing Univ. of Pot & Telecom, Chongqing, , P.R.China ABSTRACT Recently, people pay more attention to the grid technology. It can not only connect all kind of reource in the network, but alo put them into a uper tranparent computing environment for cutomer to realize mete-computing which can hare computing reource. Traditional parallel computing ytem, uch a SMP(Symmetrical multiproceor) and MPP(maively parallel proceor), ue multi-proceor to raie computing peed in a cloe coupling way, o the flexible and calable performance of the ytem are limited, a a reult of it, the ytem can't meet the requirement of the grid technology. In thi paper, the architecture of cluter computing ytem applied in grid node i introduced. It mainly include the following apect. Firt, the network architecture of cluter computing ytem in grid node i analyzed and deigned. Second, how to realize ditributing computing (including coordinating computing and haring computing) of cluter computing ytem in grid node to contruct virtual node computer i dicued. Lat, communication among grid node i analyzed. In other word, it dicue how to realize ingle reflection to let all the ervice requirement from cutomer be met through ending to the grid node. Keyword: Cluter computing, Grid node, Ditribute computing 1. INTRODUCTION In the computing world, there are many area where requirement for computation rate exceed actual proceing capability greatly. Therefore, a ingle PC(peronal computer), even which poee peak level of progreing peed and high communication performance, in t able to meet the increaing requirement of uper large cale computing. With the development of technology, cluter computing i becoming a widely accepted alternative method of providing higher availability and calability uing maintream computing product than what can be provided by a ingle ytem. The phyical model of cluter i a follow [1] : MB P/C MB P/C LM LM Bridge Bridge LD IOB LD IOB NIC NIC (WKHUQHW $70 Figure 1 The phyical model of cluter *maoyj@cqupt.edu.cn; phone Photonic North 2004: Photonic Application in Telecommunication, Senor, Software, and Laer, edited by J. Armitage, R. Leard, G. Lampropoulo, Proc. of SPIE Vol (SPIE, Bellingham, WA, 2004) X/04/$15 doi: /

2 Nowaday, there are five parallel computer model. Of thoe model, cluter architecture ha many benefit. We make a comparion among them. Firt, the architecture [1] i compared. Node Complexity Ditributed Computer Syten Cluter SMP MPP Single-Sytem Image Figure 2 The architecture comparion Second, the calable performance [1] i compared. Scalable Performance MPP The progre of the future SMP Cluter UP Fault-Tolerant Sytem Sytem Availability Figure 3 Comparion of the different computer in calable performance From the comparion above, we can make a concluion that the cluter computing ytem will be a promiing ytem and ued a an important way to realize virtual computer in future. The cluter ytem involved differ in tyle and architecture from the baic ytem which comprie the node of the cluter a well a the manner in which the node participate in the cluter ytem a a whole. Cluter computing can olve many problem in our life. The architecture of the cluter computing i et forth and grid application in cluter computing ytem i dicued in thi paper. 2. THE ARCHITECTURE OF CLUSTER COMPUTING SYSTEM A cluter i a collection of complete computer(node), and they are phyically interconnected by high-performance network or local-area network(lan). Typically, each computer node i a SMP erver, or a worktation, or a peronal computer. More importantly, all cluter node mut be able to work together collectively a a ingle, integrated computing reource, in addition to filling the conventional role of uing each node by interactive uer individually. A hown in Figure 4 [2], each node i connected through commodity or proprietary network. Thee node are complete Proc. of SPIE Vol

3 computer. They are looely coupled. In the looely coupled ytem, meage tranfer among node through connected network. The node of the cluter can expand to everal hundred node. The calable performance can be obtained through the following formula. Programming Environment and Application Availability and Single-Sytem Image Infratructure OS Node OS Node OS Node Commodity or Proprietary Interconnect Figure 4 Typical architecture of a cluter Speedup, S(n), i ued for caling the performance between ingle proceor and multi-proceor ytem. t ( n) (1) t p S = t i the time for proceing in ingle proceor ytem, tp i the time for proceing in multi-proceor(e.g., n,) ytem. The maximum of S(n) i n. a) ingle proceor b) multiproceor t ft (1-f)t equence part parallel part t p (1-f)t /n n proceor t S n) = = n t / n ( (2) Figure 5 [3] Amdahl law When data to be proceed i fixed, the time for proceing in ingle proceor ytem and in multi-proceor ytem i different. S( n) ft t + (1 f ) t n = / n 1+ ( n 1) f = (3) S( n) = 1/ f n (4) When data to proce i fixed, the maximum of S(n) i limited to n. If time to proce i fixed, the reult of S(n) i 630 Proc. of SPIE Vol. 5579

4 different. Aume i the time to proce equential part, p i the time to proce parallel part. Aume +p 1, then + p 1 S( n) = = + p / n + (1 ) / n (5) + np S( n ) = = + np = n + (1 n) + p (6) 3. GRID APPLICATION IN CLUSTER COMPUTING SYSTEM Unlike many academic/reearch-related olution, currently available grid computing olution aim to addre computational need of firm focuing on real problem acro the financial ervice ector. By being better able to olve computationally demanding problem, organization can conduct buine in a more efficient manner. Ditributed computing i moving from today' batch proceing (in which typically a ingle large tak i parceled out) to more ophiticated application and ervice crunching through a et of related tak that will require even bigger and marter virtual upercomputer. By focuing on an application environment and viewing all of the ytem in the network a a pool of available reource, grid computing oftware make application behave a if they are elf-managing, elf-healing and highly available, by intelligent ue of thi pool of reource. Target Application Type GridServer Client (Application Enabler) Manager Dektop Linux Server Linux Server Worktation Mainframe NT Server Unix SMP Server Databae Server Figure 6 Grid application In Figure 6 [4], Grid-Server reide in between the computing and torage capabilitie of the ytem and the actual application with the goal of enabling the application to take advantage of the ytem underlying computing power. Grid-Server i built on tightly integrated functional component that perform the following function: Proc. of SPIE Vol

5 Ditribute the work from the variou application to the variou reource on the network. Aggregate all of the diparate reource o that they appear to be a ingle, virtual, high-performance, fault-tolerant or reilient pool of reource to jointly upport the impoed workload. Create a unified or federated, elf-managing, ditributed or grid computing infratructure baed on the organization heterogeneou computing aet. When the job running in the cluter, different job mut be cheduled correctly. Table 1 Job Scheduling Iue for Cluter node Iue Scheme Key Problem Job priority Non-preemptive Delay of high-priority job Reource required Reource haring Scheduling Competing Static Dynamic Dedicated Space haring Time haring Independent Gang cheduling Stay Migrate Load imbalance Overhead Poor utilization Tilling, large job Proce-baed job control Severe lowdown Implementation difficulty Local job lowdown Migration threhold In the cluter, two problem are important. One i job cheduling [1], and the other i communication. In the above text, job cheduling ha been dicued. Next, the communication will be dicued. Switch Control Unit 1 n I N P U T O U T P U T 1 n DeMux Optical Buffer Wavelength Converter Mux Figure 7 [5] OPS node architecture The node of cluter tranfer meage through optical packet witching(ops). In the figure 7, OPS node architecture i hown in detail. In figure 6, when a large amount of data need to be proceed, grid-erver can make good ue of variou 632 Proc. of SPIE Vol. 5579

6 reource in order to fulfill tak in an effective way. So grid-erver can realize ditributed computing among grid node. In grid computing, the link between application and the phyical grid infratructure i provided by a middleware. It i the middleware' tak to addre mot of the requirement of ditributing computing. Due to the huge variety of project, the following lit can only be a ubet of the middleware package ued in cience: The mot common oftware component in grid computing today i the Globu toolkit. Cactu i a higher-level middleware targeted more at computing grid project than data grid. Legion fall into the ame category a Globu, but aim more at generating the illuion of a ingle, ditributed computer. Unicore allow for eamle interoperation of upercomputer over WAN(wide area network). The Sun Grid Engine i a commercial GRID middleware, incorporating many of the feature of a load leveler Traditionally, in local compute cluter, the tak of ending information from one node to another ha been handled with by the Meage Paing Interface(MPI). There i an implementation of MPI, called MPICH-G that ue the Globu toolkit for authentication. It doen't fall into the category of middleware, but hould be mentioned here due to it importance in computing grid. Baically it allow to treat a grid environment a a local cluter, albeit with a larger latency. In the following figure, middleware layer will be hown. Uer Application Workload Generation, Viualiation... Middleware Tool,Service,API,Framework Dicovery, Mapping, Scheduling, Security, Accounting... Grid Reource Computing, Storage, Intrumentation... Figure 8 Middleware-Key interface between application layer& reource layer A hown in the above figure, middleware i key interface between application and reource. It can realize the communication among grid node. When parallel computing i running in the cluter, MPI i ued for building a parallel programming environment. If a cluter which ha n node i built, tet can be run in the cluter. Firt, MPI program i debugged. It run in the following tep. Proc. of SPIE Vol

7 MPI program C C++ or Fortran MPI.exe program copy MPI.exe program to each node node 1 node 2 node n parallel computing, fulfill the tak end Figure 9 The execute proce of the MPI program When a program computing ± run in the cluter of n node, different concluion can be drawn dx = arctan( x) x π 4 = arctan(1) arctan(0) = Aume: f ( x) =, then x 1 0 f ( x) dx = π (7) We can think ± of the um of f(x), where x i from 0 to 1. N 1 π = lim f ( x) (8) n i= 1 N In the above formula, i 1 2i 1 x = = (9) N 2N 2N N 2i N i 0.5 π = lim f ( ) f ( ) (10) n i= 1 2N N N i= 1 N When the ± program run in a PC1 whoe CPU i 500MHz, PC2 whoe CPU i CPU=400MHz 70 CPU=400MHz CPU=500MHz CPU=500MHz CPU=1.7GHz CPU=1.7GHz computing tep Figure 10(a) The executing time for different node 20 computing tep Figure 10(b) The running time for different node 634 Proc. of SPIE Vol. 5579

8 1.7GHz and a PC3 whoe CPU i 400MHz, the executing time i a follow. From the above figure, we can draw a concluion that the computing time for different node i different. 4. CONCLUSION It hould have become clear by now that grid computing i till very much work in progre and, in ome way, a buzz word. While, thank to the involvement of many commercial and non-commercial intitution, it i afe to conclude that grid computing will play an important role in future. The paper ha mainly analyed uper computing environment being tranparent to uer can be applied in grid node, which adopt cluter computing ytem architecture and connect all the computing reource through network. The forming uper computing environment can be ued to realize meta-computing and contruct node virtual computer, and alo carry out ditributed computing including coordinating computing and haring computing. At lat, how to realize communication among grid node through ingle ytem image to meet all the ervice requirement from cutomer i dicued. We believe that with the development of the technology, grid application will be taken to the next level. ACKNOWLEDGEMENT Thi work ha been upported by the Science Technology Development Foundation of China Information Indutry Minitry, Project NO:01XK The author wih to thank all the partner of the project. REFERENCES 1. Kai Hwang and Zhiwei Xu, Scalable Parallel Computing, China Machine Pre. May Rajkumar Buyya, High Performance Cluter Computing: Architecture and Sytem, Pot & Telecommunication Pre. Augut, Barry Wilkinon and Michael Allen. Parallel Programming: Technique and Application Uing Networked Worktation and parallel Computer. Prentice Hall, Inc., DataSynape, Uing grid computing to create a virtual environment for application, April, George N. Rouka, Liong Xu. OPTICAL PACKET SWITCHING. Department of Computer Science, North Carolina State Univerity, April 2004 Proc. of SPIE Vol