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Overview of Supercomputers
Presented by:Mehmet Demir
20090694ENG-102
Table of Contents Introduction What are They Used For How Do They Differ From a Personal Computer? Where Are They Now Main Parts of Supercomputers Processor Types Conclusion References
Supercomputers
The category of computers that includes the fastest and most powerful (most expensive) ones available at any given time.
Designed to solve complex mathematical equations and computational problems very quickly.
What are They Used For Climate prediction & Weather forecasting
What are They Used For (cont.)
Computational chemistry Crash analysis Cryptography Nuclear simulation Structural analysis
How Do They Differ From a Personal Computer Cost
range from $100,000s to $1,000,000s Environment
most require environmentally controlled rooms Peripherals
lack sound cards, graphic boards, keyboards, etc. accessed via workstation or PC
Programming language FORTRAN
History
Seymour Cray (1925-1996) Developed CDC 1604 – first fully transistorized
supercomputer (1958) CDC 6600 (1965), 9 MFlops Founded Cray Research in 1972 (now Cray Inc.)
CRAY-1 (1976), $8.8 million, 160 MFlops CRAY-2 (1985) CRAY-3 (1989)
Early Timeline of SupercomputersPeriod Supercomputer Peak speed Location
1943-1944 Colossus 5000 characters per second Bletchley Park, England
1945-1950 Manchester Mark I 500 instructions per second University of Manchester, England
1950-1955 MIT Whirlwind20 KIPS (CRT memory)40 KIPS (Core)
Massachusetts Institute of Technology, Cambridge, MA
1956-1958 IBM 70440 KIPS12 kiloflops
1958-1959 IBM 70940 KIPS12 kiloflops
1959-1960 IBM 7090 210 kiloflops U.S. Air Force BMEWS (RADC), Rome, NY
1960-1961 LARC 500 kiloflops (2 CPUs) Lawrence Livermore Laboratory, California
1961-1964 IBM 7030 "Stretch"1.2 MIPS~600 kiloflops
Los Alamos National Laboratory, New Mexico
1965-1969 CDC 660010 MIPS3 megaflops
Lawrence Livermore Laboratory, California
1969-1975 CDC 7600 36 megaflops Lawrence Livermore Laboratory, California
1974-1975 CDC Star-100100 megaflops (vector),~2 megaflops (scalar)
Lawrence Livermore Laboratory, California
1975-1983 Cray-180 megaflops (vector),72 megaflops (scalar)
Los Alamos National Laboratory, New Mexico (1976)
1975-1982 ILLIAC IV150 megaflops,<100 megaflops (average)
NASA Ames Research Center, CaliforniaHad serious reliability problems.
1981-1983 CDC Cyber-205400 megaflops (vector),average much lower.
1983-1985 Cray X-MP 500 megaflops (4 CPUs) Los Alamos National Laboratory, New Mexico
1985-1990 Cray-21.95 gigaflops (4 CPUs)3.9 gigaflops (8 CPUs)
Lawrence Livermore Laboratory and NASALawrence Berkeley National Laboratory (the only 8 CPU system)
1989-1990 ETA-10G10.3 gigaflops (vector) (8 CPUs),average much lower.
1990-1995 Fujitsu Numerical Wind Tunnel
236 gigaflops National Aerospace Lab
1995-2000 Intel ASCI Red 2.15 teraflops Sandia National Laboratories, New Mexico
2000-2002IBM ASCI White, SP Power3 375 MHz
7.226 teraflops Lawrence Livermore Laboratory, California
2002-2004 Earth Simulator 35.86 teraflops Yokohama Institute for Earth Sciences, Japan
2004-Blue Gene/L prototype
70.72 teraflops✝ IBM, Rochester, Minnesota[2]
Where Are They Now
www.top500.org List released twice a year Scores based on Linpack benchmark Solve dense system of linear equations Speed measured in floating point operations
per second (FLOPS)
Architectures - SMP Symmetric Shared-
Memory Multiprocessing (SMP) Share memory Common OS Programs are divided
into subtasks (threads) among all processors (multithreading)
Architectures – MPP Massively Parallel Processing (MPP)
Individual memory for each processor Individual OS’s Messaging interface for communication 200+ processors can work on same application
1. A large retailer wants to know how many camcorders the company sold in
1998, and sends that query to the MPP system. 2. The query goes out to one of the processors which acts as the
coordinator, it breaks up the query for optimum performance. For example, it could break the query up by month; this “sub-query”
then goes to all the processors at the same time.
3. Each sub-query is assigned to a specific processor in the system. To allow this to happen, the database was previously partitioned. For example, a sales tracking database might be broken down by month, and
each processor holds data for one month’s worth of sales information. 4. The responses to the queries are returned to a processor to be coordinated—for
example, each month is added up 5. Final answer is returned to the user.
Architectures – Clustering
Grid computing Many servers connected together Relies heavily on network speed Easily upgraded with addition of more
servers
Processor Types
Vector processing Expensive NEC Earth Simulator
Scalar processing Grid computing
Based on off the shelf parts (ordinary CPUs)
BlueGene/L
IBM MPP (massively parallel processing) #1 on top500 as of November 2004 32,768 processors (700Mhz) 70.72 Teraflops (trillions of FLOPS) Runs linux DNA, climate simulation, financial risk Cost more than $100 million
BlueGene/L System Layout
2 Processors Node communication Mathematical calculations
BlueGene/L Compute Card
BlueGene/L Node Board
BlueGene/L Cabinet
Some of the Others
#2 - Columbia (NASA, USA) – 51.87 TFlops #3 - Earth Simulator (Japan) – 35.86 TFlops #4 - MareNostrum (Spain) – 20.53 TFlops #5 - Thunder (USA) – 19.94 TFlops
The Future
References http://www.top500.org/ http://www.pcquest.com/content/Supercomputer/
102051004.asp http://news.com.com/2100-1008_3-1000421.html?
tag=fd_lede2_hed http://www.research.ibm.com/bluegene/index.html http://www.llnl.gov/asci/platforms/bluegene/papers/
2hardware_overview.pdf http://www.hpce.nec.com/451+M5f7cd421b8e.0.html http://www.cray.com/about_cray/history.html http://www.serc.iisc.ernet.in/~govind/243/L7-PA-Intro.pdf http://www.computerworld.com/hardwaretopics/
hardware/server/story/0,10801,43504,00.html