Introduction of Cluster and (KBRIN) Computational Cluster Facilities Xiaohui CECS Department University of Louisville X 0 cui 001@uofl. edu 09/03/2003
Introduction to Cluster Technology What is a Beowulf ? Kentucky Biomedical Research Infrastructure Network MPI Programming on KBRIN cluster
People always wants to have faster computer • Normal users – Play game faster – Play music better, watch movies better • Science and Engineer – Solving larger and more complex science and engineering problems using computer modeling, simulation and analysis
How to make a computer faster? • Make a faster chip! – reduce feature size – better architecture, better memory subsystem • VLIW , Super scalar, vector support, DSP instruction (MMX, 3 DNow) • SDRAM, NVRAM • Uni-processor speed is still limited by speed of light • Alternate technologies – Optical – Bio – Molecular
How to make a computer faster? • Using multiple processors to solve a single problem – Divide problem into many small pieces – Distributed these small problems to be solved by multiple processors simultaneously • This technique is called Parallel Processing
Parallel computer • Parallel computer is a special computer with – High Speed I/O , Large memory, multiple processing units, fast communication network • Every modern supercomputer is also a parallel computer CPU CPU High Speed Network
Fastest Supercomputer in the world • Intel ASCI Red at Sandia National Laboratory • 9216 Pentium Processors • 2. 3 Teraflops performance
But Supercomputer will cost you 100 millions, how to get enough money to buy one? • Using PC Cluster is a low cost solution to this problem
Introduction to Cluster Technology • A Cluster system is – Parallel multi-computer built from high-end PCs and conventional high-speed network.
Why cluster computing? • Scalability – Build small system first, grow it later. • Low-cost – Hardware based on COTS model (Component off-the-shelf) – Software based on freeware from research community • Easier to maintain • Vendor independent
Different kinds of PC cluster • High Performance Computing Cluster • Load Balancing • High Availability
The Beginning • Thomas Sterling and Donald Becker CESDIS, Goddard Space Flight Center, Greenbelt, MD • Summer 1994: built an experimental cluster • Called their cluster Beowulf • 16 x 486 DX 4, 100 MHz processors • 16 MB of RAM each, 256 MB in total • Channel bonded Ethernet (2 x 10 Mbps) • Not that different from our Beowulf
Current Beowulfs • Faster processors, faster interconnect, but the idea remains the same • Cluster database: http: //clusters. top 500. org/db/Query. php 3 • Super cluster: 2300 processors, 11 TFLOPS peak
What is a Beowulf ? • Runs a free operating system (not Wolfpack, MSCS) • Connected by high speed interconnect • Compute nodes are dedicated (not Network of Workstations)
Why Beowulf? • It’s cheap! • Our Beowulf, 32 processors, 32 GB RAM: $50, 000 • The IBM SP 2 cluster cost many millions • Everything in a Beowulf is open-source and open standard - easier to manage/upgrade
Essential Components of a Beowulf • Processors • AMD and Intel • Memory • DDR RAM • RDRAM • Interconnect • Fast Ethernet • Gigabit Ethernet • Myrinet • Software
Free cluster OS and management software • OS • Linux • Free. BSD • Cluster Management • Oscar: http: //oscar. sourceforge. net/ • Rocks: http: //rocks. npaci. edu • MOSIX: http: //www. mosix. org/
DIY Cluster
White Box Desktop n Cheap n n n Expandable n n n 4 -6 PCI slots 3 -5 disk drives Low density n n 2. 8 GHz Pentium 4 for $1000 Very low margins 16 processor in on rack (on shelves) Quality n 90 - 365 day warrantees
Commercial designed Cluster
Brand Name Servers n Expensive n n High density n n Up to double equivalent desktop hardware Rack mountable 64 processors in one rack Blades Quality n 3 year warrantee n n Throw away machine when out of warrantee Good thermal design
Minimum Components Power Local Hard Drive Ethernet x 86 server
Cluster Advantages • Error isolation: separate address space limits contamination of error • Repair: Easier to replace a machine without bringing down the system than in an shared memory multiprocessor • Scale: easier to expand the system without bringing down the application that runs on top of the cluster • Cost: Large scale machine has low volume => fewer machines to spread development costs vs. leverage high volume off-the-shelf switches and computers • Amazon, AOL, Google, Hotmail, Inktomi, Web. TV, and Yahoo rely on clusters of PCs to provide services used by millions of people every day
Cluster Drawbacks • Cost of administering a cluster of N machines ~ administering N independent machines vs. cost of administering a shared address space N processors multiprocessor ~ administering 1 big machine • Clusters usually connected using I/O bus, whereas multiprocessors usually connected on memory bus • Cluster of N machines has N independent memories and N copies of OS, but a shared address multi-processor allows 1 program to use almost all memory
Google company 2001 cluster reliability statistic • For 6000 PCs, 12000 HD, 200 EN switches • ~ 20 PCs will need to be rebooted/day • ~ 2 PCs/day hardware failure, or 2%-3% / year – 5% due to problems with motherboard, power supply, and connectors – 30% DRAM: bits change + errors in transmission (100 MHz) – 30% Disks fail – 30% Disks go very slow (10%-3% expected BW) • 200 EN switches, 2 -3 fail in 2 years
Kentucky Biomedical Research Infrastructure Network (KBRIN) Computational Cluster Facilities CECS Department Bioinformatics Laboratory KBRIN Computational Cluster Dahlem Supercomputer Laboratory KBRIN Supercomputer HP Laser Printer Dual AMD 2400 Workstation 2 GB memory (4) 70 GB hard drives 100 mb NIC Dual AMD 2400 2 GB memory 40 GB hard drive 1 gb NIC Dual AMD 2400 Workstation 2 GB memory 80 GB hard drive 100 mb and 1 gb NIC Web Srvr / Bkp master Dual AMD 2400 2 GB memory CD RW drive (4) 70 GB hard drives 100 mb and 1 gb NIC 100 mb Ethernet Gigabit Ethernet Dual AMD 2400 Workstation 2 GB memory 80 GB hard drive 100 mb and 1 gb NIC Master Backup System (16) Compute Nodes Dual AMD 2400 Workstation 2 GB memory 80 GB hard drive 100 mb and 1 gb NIC KBRIN Project Office KVM Switch Monitor, Keyboard Master Node Dual AMD 2400 2 GB memory CD RW drive (4) 70 GB hard drives 100 mb and 1 gb NIC 24 Port Gb Ethernet Switch 100 mb Ethernet Campus Ethernet Network Elb 4/1/2003
Programming a Cluster • Cluster power comes from parallel processing – Large task is decomposed to a set of small tasks – These tasks are executed by a set of processes on multiple nodes • Programming model based on Message Passing – These process communicate by exchanging message which consists of data and synchronization information
Programming environments • Threads (PCs, SMPs, NOW. . ) – POSIX Threads – Java Threads • MPI – http: //www-unix. mcs. anl. gov/mpich/ • PVM – http: //www. epm. ornl. gov/pvm/
MPI n n Message Passing Interface v 1. 1, v 2. 0 n Standard for high performance message passing on parallel machines n http: //www-unix. mcs. anl. gov/mpi/ Supports n GNU C, Fortran 77 n Intel C, Fortran 77, Fortran 90 n Portland Group C, C++, Fortran 77, Fortran 90 n Requires site license
PVM n Parallel Virtual Machines v 3. 4. 3 n Message passing interface for heterogeneous architectures n Supports over 60 variants of UNIX n Supports Windows NT n Resource control and meta computing n Fault tolerance n http: //www. csm. ornl. gov/pvm/
MPI Programming A 2 6 2 8 1 2 2 4 43 87 3 9 5 6 3 8 3 5 9 1 5 8 4 0 9 9 5 1 5 24 8 9 1 5 5 6 8 6 6 2 67 8 9 5 63 6 7 4 4 2 8 8 4 4 3 1 2 7 1 9 1 8 Sum(A)=?
MPI Programming 2 6 A 1 2 8 1 A 3 2 2 4 43 87 3 9 5 3 3 9 6 8 5 1 5 8 4 0 9 9 5 1 6 2 24 8 5 A 2 5 6 6 67 8 56 6 4 3 A 4 2 8 4 4 1 2 9 8 9 7 4 8 3 7 Sum(A 1, A 2, A 3, A 4)=? 1 9 1 8
MPI Programming Request Output Master Slaves
MPI Programming /* Algorithm for the master program */ initialize the array `items'. /* send data to the slaves */ for i = 0 to 3 Send items[25*i] to items[25*(i+1)-1] to slave Pi end for /* collect the results from the slaves */ for i = 0 to 3 Receive the result from slave Pi in result[i] end for /* calculate the final result */ sum = 0 for i = 0 to 3 sum = sum + result[i] end for print sum
MPI Programming /* Algorithm for the slave program */ Receive 25 elements from the master in some array say `items' /* calculate intermediate result */ sum = 0 for i = 0 to 24 sum = sum + items[i] end for send `sum' as the intermediate result to the master
Run MPI Program on the Cluster • MPI C compiler: mpicc • MPI job submit software: PBS • The PBS command used for submit MPI job: • Mkpbs • Qsub • Rps
Portable Batch System n Three standard components to PBS n MOM n Daemon on every node n Used for job launching and health reporting n Server n On the frontend only n Queue definition, and aggregation of node information n Scheduler n Policies for what job to run out of which queue at what time
Connect cluster from your computer
Free X-windows Server on windows http: //www. cygwin. com/
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