|
|
| (One intermediate revision by one other user not shown) |
| Line 1: |
Line 1: |
| {{Other uses|Flop (disambiguation){{!}}Flop}}
| | <br><br>Sports betting can be a particularly thrilling and rewarding journey in the event you apply it accurately and decrease your chances of shedding your bets. Whereas betting the purpose spread offers with which team will win and by what number of factors or scores, betting cash strains is completely involved with which group will win a particular howtobetonsports101.com sport or event. Google Android is without doubt one of the hottest Operating Techniques for Smartphones available on the market. |
| {| class="infobox"
| |
| |+ Computer performance
| |
| ! Name
| |
| ! FLOPS
| |
| |-
| |
| ! [[Yotta-|yotta]]FLOPS
| |
| | 10<sup>24</sup>
| |
| |-
| |
| ! [[Zetta-|zetta]]FLOPS
| |
| | 10<sup>21</sup>
| |
| |-
| |
| ! [[Exa-|exa]]FLOPS
| |
| | 10<sup>18</sup>
| |
| |-
| |
| ! [[Peta-|peta]]FLOPS
| |
| | 10<sup>15</sup>
| |
| |-
| |
| ! [[Tera-|tera]]FLOPS
| |
| | 10<sup>12</sup>
| |
| |-
| |
| ! [[Giga-|giga]]FLOPS
| |
| | 10<sup>9</sup>
| |
| |-
| |
| ! [[Mega-|mega]]FLOPS
| |
| | 10<sup>6</sup>
| |
| |-
| |
| ! [[Kilo-|kilo]]FLOPS
| |
| | 10<sup>3</sup>
| |
| |}
| |
|
| |
|
| In [[computing]], '''FLOPS''' (for '''FL'''oating-point '''O'''perations '''P'''er '''S'''econd) is a measure of [[computer performance]], useful in fields of scientific calculations that make heavy use of [[floating-point]] calculations. For such cases it is a more accurate measure than the generic [[instructions per second]].
| | First released in 2007, this cellular platform has taken a chunk out of iPhone, Blackberry and Home windows Cell to turn into one of the high promoting smartphones. Learn the newest Google android critiques and new consumer tips, plus info on Google Android apps and market news at . Hello all. May you guys inform me how am i able to sports betting get gunstringer code in Fruit Ninja Kinect? Have you got gunstringer code in Fruit Ninja Kinect? |
|
| |
|
| Since the final ''S'' stands for "second", conservative speakers consider "FLOPS" as both the singular and plural of the term, although the singular "FLOP" is frequently encountered. Alternatively, the singular '''FLOP''' (or '''flop''') is used as an abbreviation for "'''FL'''oating-point '''OP'''eration", and a flop count is a count of these operations (e.g., required by a given algorithm or computer program). In this context, "flops" is simply the plural rather than a rate, which would then be "flop/s". The expression 1 flops is actually interpreted as <math>f_{\text{flop}} = 1\,\mathrm{s}^{-1}\,\Leftrightarrow\, n_{\text{flops}} = 1</math>.
| | If you already know, please give me a guide to get gunstringer code in Fruit Ninja Kinect. A lot appreciated! Additionally, take a look at - Quit Smoking Now with Max Kirsten (see references for obtain hyperlink) plus more apps to help you to Quit Smoking with your iPhone The Parlay is a method to bet on multiple sporting events with hope for an enormous payoff if all of them win. With parlay cards, all picks are relative to the point spread. |
|
| |
|
| ==Computing ==
| | If just one occasion would not win or draw you then lose your complete bet. If a number of occasion is a draw then these occasions are ignored. In case you win all the other events you receives a commission in keeping with the number of events that you did win. In the event all games bet on result in a push except one or none then all the bet becomes a push. The next desk shows the home edge for varied number of picks and pays assuming a random picker. |
| One can calculate FLOPS using this equation:<ref name="en.community.dell.com">[http://en.community.dell.com/techcenter/high-performance-computing/w/wiki/2329.aspx "Nodes, Sockets, Cores and FLOPS, Oh, My" by Dr. Mark R. Fernandez, Ph.D.]</ref>
| |
|
| |
|
| :<math>\text{FLOPS} = \text{cores} \times \text{clock} \times \frac{\text{FLOPs}}{\text{cycle}}</math>
| | GTbets - Online Sports Betting and Casino Chief With numerous sports and horse racing traces together with a wide range of casino games, GTbets is a top vacation spot for those seeking a comprehensive gaming expertise. In addition to variety, GBbets can also be well known for providing frequent promotions, quick and straightforward deposits/cashouts, wonderful customer assist and Recreation Time Rewards - one of the vital generous rewards packages in the gaming business. |
|
| |
|
| Most microprocessors today can do 4 FLOPs per clock cycle.<ref name="en.community.dell.com"/> Therefore, a single-core 2.5 GHz processor has a theoretical performance of 10 billion FLOPS = 10 [[giga-|G]]FLOPS.
| | Preserve reading to find out extra about Game Tim eRewards and the other highlights of GTbets. The 2011 French Open guarantees to be one of the competitive in recent years and spread bettors will be weighing up whether or not Novak Djokovic can take Rafael Nadal's crown at Roland Garros. Given the Spaniard's outstanding file in Paris, he deserves to be on the high of the Sporting Index match index once more this 12 how to make sports bet months. Nevertheless, those trying to sell Nadal's outright event index may have been fascinated to see that Djokovic has not too long ago gained on the Madrid and Rome Masters occasions. |
|
| |
|
| Note: In this context, ''sockets'' is referring to chip sockets on a motherboard, in other words, how many computer chips are in use, with each chip having one or more cores on it. This equation only applies to one very specific (but common) hardware architecture and it ignores limits imposed by memory bandwidth and other constraints. In general, GigaFLOPS are not determined by theoretical calculations such as this one; instead, they are measured by actual benchmarks of actual performance/throughput. Because this equation ignores all sources of overhead, in the real world, one will never get actual performance that is anywhere near to what this equation predicts.
| | learn extra |
| | |
| == Records ==
| |
| | |
| ===Single computer records===
| |
| In late 1996, [[Intel]]'s [[ASCI Red]] was the world's first computer to achieve one TFLOPS and beyond. Sandia director Bill Camp said that ASCI Red had the best reliability of any supercomputer ever built, and “was supercomputing’s high-water mark in longevity, price, and performance.”
| |
| <ref name="jacobsequity.com">{{cite web|title=Sandia’s ASCI Red, world’s first teraflop supercomputer, is decommissioned |url=http://www.jacobsequity.com/ASCI%20Red%20Supercomputer.pdf|accessdate=17 November 2011}}</ref>{{dead link|date=November 2012}}
| |
| | |
| [[NEC]]'s [[NEC SX-9|SX-9]] supercomputer was the world's first [[vector processor]] to exceed 100 gigaFLOPS per single core.
| |
| | |
| For comparison, a handheld [[calculator]] performs relatively few FLOPS. A computer response time below 0.1 second in a calculation context is usually perceived as instantaneous by a human operator,<ref>{{cite web |url=http://www.useit.com/papers/responsetime.html |title=Response Times: The Three Important Limits |accessdate=June 11, 2008 |publisher=Jakob Nielsen}}</ref> so a simple calculator needs only about 10 FLOPS to be considered functional.
| |
| | |
| In June 2006, a new computer was announced by Japanese research institute [[RIKEN]], the [[MDGRAPE-3]]. The computer's performance tops out at one petaFLOPS, almost two times faster than the Blue Gene/L, but MDGRAPE-3 is not a general purpose computer, which is why it does not appear in the Top500.org list. It has special-purpose [[pipeline (computing)|pipelines]] for simulating molecular dynamics.
| |
| | |
| By 2007, [[Intel Corporation]] unveiled the experimental [[multi-core]] [[Teraflops Research Chip|POLARIS]] chip, which achieves 1 TFLOPS at 3.13 GHz. The 80-core chip can raise this result to 2 TFLOPS at 6.26 GHz, although the thermal dissipation at this frequency exceeds 190 watts.<ref>{{cite web|author=Published on 30th April 2007 by Richard Swinburne |url=http://www.bit-tech.net/hardware/2007/04/30/the_arrival_of_teraflop_computing/2 |title=The Arrival of TeraFLOP Computing |publisher=bit-tech.net |date=2007-04-30 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| | |
| On June 26, 2007, [[IBM]] announced the second generation of its top supercomputer, dubbed Blue Gene/P and designed to continuously operate at speeds exceeding one petaFLOPS. When configured to do so, it can reach speeds in excess of three petaFLOPS.<ref>{{cite news|url=http://www.top500.org/lists/2008/06|title=June 2008|publisher=TOP500|accessdate=July 8, 2008}}</ref>
| |
| | |
| In June 2007, Top500.org reported the fastest computer in the world to be the [[Blue Gene|IBM Blue Gene/L]] supercomputer, measuring a peak of 596 teraFLOPS.<ref>{{cite news|url=http://top500.org/news/2007/06/23/29th_top500_list_world_s_fastest_supercomputers_released|title=29th TOP500 List of World's Fastest Supercomputers Released|date=June 23, 2007|publisher=Top500.org|accessdate=July 8, 2008}}</ref> The [[Cray XT4]] hit second place with 101.7 teraFLOPS.
| |
| | |
| On October 25, 2007, [[NEC]] Corporation of Japan issued a press release<ref>{{cite news|url=http://www.nec.co.jp/press/en/0710/2501.html|title=NEC Launches World's Fastest Vector Supercomputer, SX-9|date=October 25, 2007|publisher=NEC|accessdate=July 8, 2008}}</ref> announcing its SX series model [[SX-9]], claiming it to be the world's fastest vector supercomputer. The [[SX-9]] features the first CPU capable of a peak vector performance of 102.4 gigaFLOPS per single core.
| |
| | |
| On February 4, 2008, the [[National Science Foundation|NSF]] and the [[University of Texas]] opened full scale research runs on an [[AMD]], [[Sun Microsystems|Sun]] supercomputer named [[Texas Advanced Computing Center#Ranger|Ranger]],<ref>
| |
| {{cite web
| |
| | url = http://www.tacc.utexas.edu/resources/hpcsystems/
| |
| | title = University of Texas at Austin, Texas Advanced Computing Center
| |
| | accessdate = September 13, 2010
| |
| | quote = Any researcher at a U.S. institution can submit a proposal to request an allocation of cycles on the system.
| |
| }}</ref>
| |
| the most powerful supercomputing system in the world for open science research, which operates at sustained speed of half a petaFLOPS.
| |
| | |
| On May 25, 2008, an American supercomputer built by [[IBM]], named '[[IBM Roadrunner|Roadrunner]]', reached the computing milestone of one petaflops by processing more than 1.026 [[1,000,000,000,000,000|quadrillion]] calculations per second. It headed the June 2008<ref>{{cite web
| |
| |url=http://www.computerworld.com/action/article.do?command=viewArticleBasic&taxonomyName=hardware&articleId=9095318&taxonomyId=12&intsrc=kc_top
| |
| |title=IBM's Roadrunner smashes 4-minute mile of supercomputing
| |
| |accessdate=June 10, 2008
| |
| |author=Sharon Gaudin
| |
| |date=June 9, 2008
| |
| |publisher=Computerworld
| |
| }}</ref> and November 2008<ref>{{cite web|url=http://www.top500.org/lists/2008/11/press-release |title=Austin ISC08 |publisher=Top500.org |date=2008-11-14 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> [[TOP500]] list of the most powerful supercomputers (excluding [[grid computing|grid computers]]). The computer is located at Los Alamos National Laboratory in New Mexico, and the computer's name refers to the New Mexico [[List of U.S. state birds|state bird]], the [[Greater Roadrunner]].<ref>{{cite news|url=http://news.bbc.co.uk/1/hi/technology/7443557.stm|title=Supercomputer sets petaflop pace |last=Fildes|first=Jonathan |date=June 9, 2008|publisher=BBC News|accessdate=July 8, 2008}}</ref>
| |
| | |
| In June 2008, AMD released ATI Radeon HD4800 series, which are reported to be the first GPUs to achieve one teraFLOPS scale. On August 12, 2008 AMD released the ATI Radeon HD 4870X2 graphics card with two [[Radeon R770]] GPUs totaling 2.4 teraFLOPS.
| |
| | |
| In November 2008, an upgrade to the Cray XT Jaguar supercomputer at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) raised the system's computing power to a peak 1.64 “petaflops,” or a quadrillion mathematical calculations per second, making Jaguar the world’s first petaflops system dedicated to open research. In early 2009 the supercomputer was named after a mythical creature, [[Kraken]]. Kraken was declared the world's fastest university-managed supercomputer and sixth fastest overall in the 2009 [[TOP500]] list, which is the global standard for ranking supercomputers. In 2010 Kraken was upgraded and can operate faster and is more powerful.
| |
| | |
| In 2009, the [[Cray]] Jaguar performed at 1.75 petaFLOPS, beating the [[IBM]] [[IBM Roadrunner|Roadrunner]] for the number one spot on the [[TOP500]] list.<ref>{{cite news| url=http://www.forbes.com/2009/11/15/supercomputer-ibm-jaguar-technology-cio-network-cray.html?feed=rss_popstories | work=Forbes | first=Andy | last=Greenberg | title=Cray Dethrones IBM In Supercomputing | date=November 16, 2009|archiveurl=http://archive.is/pivZN|archivedate=January 23, 2013}}</ref>
| |
| | |
| In October 2010, China unveiled the [[Tianhe-I]], a supercomputer that operates at a peak computing rate of 2.5 petaflops.<ref>{{cite news| url=http://www.bbc.co.uk/news/technology-11644252 | work=BBC News | title=China claims supercomputer crown | date=October 28, 2010}}</ref><ref>{{cite web|last=Dillow |first=Clay |url=http://www.popsci.com/technology/article/2010-10/china-unveils-2507-petaflop-supercomputer-worlds-fastest |title=China Unveils 2507 Petaflop Supercomputer, the World's Fastest |publisher=Popsci.com |date=2010-10-28 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| | |
| {{As of|2010}}, the fastest six-core PC [[microprocessor|processor]] reaches 109 gigaFLOPS ([[Intel Core i7]] [[Gulftown (microprocessor)|980 XE]])<ref>{{Cite journal|url=http://techgage.com/article/intels_core_i7-980x_extreme_edition_-_ready_for_sick_scores/8 |title=Intel's Core i7-980X Extreme Edition – Ready for Sick Scores?: Mathematics: Sandra Arithmetic, Crypto, Microsoft Excel |publisher=Techgage |date=2010-03-10 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> in double precision calculations. [[Graphics processing unit|GPU]]s are considerably more powerful. For example, [[Nvidia Tesla]] C2050 GPU computing processors perform around 515 gigaFLOPS<ref name="nvidia.com">{{cite web|url=http://www.nvidia.com/object/product_tesla_C2050_C2070_us.html |title=NVIDIA Tesla Personal Supercomputer |publisher=Nvidia.com |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> in double precision calculations, and the AMD FireStream 9270 peaks at 240 gigaFLOPS.<ref name="ati.amd.com">{{cite web|url=http://www.amd.com/us/products/workstation/firestream/firestream-9270/pages/firestream-9270.aspx |title=AMD FireStream 9270 GPU Compute Accelerator |publisher=Amd.com |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> In single precision performance, Nvidia Tesla C2050 computing processors perform around 1.03 teraFLOPS and the AMD FireStream 9270 cards peak at 1.2 teraFLOPS. Both Nvidia and AMD's consumer gaming GPUs may reach higher FLOPS. For example, AMD’s HemlockXT 5970<ref name=autogenerated1>http://www.amd.com/us/products/desktop/graphics/ati-radeon-hd-5000/hd-5970/Pages/ati-radeon-hd-5970-specifications.aspx</ref> reaches 928 gigaFLOPS in double precision calculations with two GPUs on board and the Nvidia GTX 480 reaches 672 gigaFLOPS<ref name=autogenerated2>{{cite web|url=http://www.nvidia.com/object/product_geforce_gtx_480_us.html |title=GeForce GTX 480 |publisher=Nvidia.com |date=2010-07-20 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> with one GPU on board.
| |
| | |
| On December 2, 2010, the US Air Force unveiled a defense supercomputer made up of 1,760 [[PlayStation 3]] consoles that can run 500 trillion floating-point operations per second.<ref>{{cite web|last=Dillow |first=Clay |url=http://www.popsci.com/technology/article/2010-12/air-forces-new-supercomputer-made-1760-playstation-3s |title=Air Force Unveils Fastest Defense Supercomputer, Made of 1760 PlayStation 3 |publisher=Popsci.com |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> (500 teraFLOPS)
| |
| | |
| In November 2011, it was announced that Japan had achieved 10.51 petaflops with its [[K computer]].<ref name="Petaflops">{{cite web|url=http://www.fujitsu.com/global/news/pr/archives/month/2011/20111102-02.html |title='K computer' Achieves Goal of 10 Petaflops |publisher=Fujitsu.com |date= |accessdate=2012-02-09}}</ref> It is still under development and software performance tuning is currently underway. It has 88,128 [[SPARC64 VIIIfx]] [[central processing unit|processor]]s in 864 racks, with theoretical performance of 11.28 petaflops. It is named after the Japanese word "[[wikt:京#Japanese|kei]]", which stands for 10 [[1,000,000,000,000,000|quadrillion]],<ref>See [[Japanese numerals#Large numbers|Japanese numbers]]</ref> corresponding to the target speed of 10 petaFLOPS.
| |
| | |
| On November 15, 2011, Intel demonstrated a single x86-based processor, code-named "Knights Corner", sustaining more than a TeraFlop on a wide range of [[DGEMM]] operations. Intel emphasized during the demonstration that this was a sustained TeraFlop (not "raw TeraFlop" used by others to get higher but less meaningful numbers), and that it was the first general purpose processor to ever cross a TeraFlop.<ref>{{cite web|url=http://www.tomshardware.com/news/intel-knights-corner-mic-co-processor,14002.html |title=Intel's Knights Corner: 50+ Core 22nm Co-processor|accessdate=November 16, 2011}}</ref><ref>{{cite web|url=http://www.eetimes.com/electronics-news/4230654/Intel-unveils-1-TFLOP-s-Knight-s-Corner |title=Intel unveils 1 TFLOP/s Knight's Corner|accessdate=November 16, 2011}}</ref>
| |
| | |
| On June 18, 2012, [[IBM Sequoia|IBM's Sequoia supercomputer system]], based at the U.S. Lawrence Livermore National Laboratory (LLNL), reached 16 petaFLOPS, setting the world record and claiming first place in the latest TOP500 list.<ref name="IBM Computer Sets Speed Record">{{cite news|last=Clark|first=Don|title=IBM Computer Sets Speed Record|url=http://online.wsj.com/article/SB10001424052702303379204577472773983130902.html|accessdate=18 June 2012|newspaper=The Wall Street Journal|date=18 June 2012}}</ref>
| |
| | |
| On November 12, 2012, the TOP500 list certified [[Titan (supercomputer)|Titan]] as the world's fastest supercomputer per the LINPACK benchmark, at 17.59 petaFLOPS.<ref>{{cite web|url=http://www.bbc.co.uk/news/technology-20272810 |title=BBC News – US Titan supercomputer clocked as world's fastest |publisher=Bbc.co.uk |date=2012-11-12 |accessdate=2013-02-28}}</ref><ref>{{cite web|url=http://top500.org/blog/lists/2012/11/press-release/ |title=Oak Ridge Claims No. 1 Position on Latest TOP500 List with Titan | TOP500 Supercomputer Sites |publisher=Top500.org |date=2012-11-12 |accessdate=2013-02-28}}</ref> It was developed by Cray Inc. at the [[Oak Ridge National Laboratory]] and combines AMD Opteron processors with “Kepler” NVIDIA Tesla graphic processing unit (GPU) technologies.<ref>{{Cite journal|last=Montalbano |first=Elizabeth |url=http://www.informationweek.com/news/government/enterprise-architecture/231900554 |title=Oak Ridge Labs Builds Fastest Supercomputer |publisher=Informationweek |date=2011-10-11 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref><ref>{{cite web|last=Tibken |first=Shara |url=http://news.cnet.com/8301-11386_3-57541791-76/titan-supercomputer-debuts-for-open-scientific-research/ |title=Titan supercomputer debuts for open scientific research | Cutting Edge – CNET News |publisher=News.cnet.com |date=2012-10-29 |accessdate=2013-02-28}}</ref>
| |
| | |
| On June 10, 2013, China's [[Tianhe-2]] was ranked the world's fastest with a record of 33.86 petaflops.<ref>{{cite web|url=http://www.forbes.com/sites/alexknapp/2013/06/17/chinese-supercomputer-is-now-the-worlds-fastest-by-a-lot/ |title=Chinese Supercomputer Is Now The World's Fastest - By A Lot|publisher=Forbes Magazine |date=2013-06-17 |accessdate=2013-06-17}}</ref>
| |
| | |
| ===Distributed computing records===
| |
| [[Distributed computing]] uses the [[Internet]] to link [[personal computer]]s to achieve more FLOPS:
| |
| | |
| * {{As of|2012|11}}, [[Great Internet Mersenne Prime Search|GIMPS]], which began in 1996, is sustaining 95 teraFLOPS.<ref>{{cite web |url=http://www.mersenne.org/primenet |title=Internet PrimeNet Server Distributed Computing Technology for the Great Internet Mersenne Prime Search |work=GIMPS |accessdate=April 15, 2012 |postscript=<!--None--> }}</ref>
| |
| | |
| * {{As of|2012|11}}, [[Einstein@Home]] is crunching more than 885.0 teraFLOPS.<ref>{{cite web |url=http://boincstats.com/en/stats/5/project/detail |title=Einstein@Home Credit overview |publisher=BOINC |accessdate=April 15, 2012}}</ref>
| |
| | |
| * {{As of|2012|11}}, [[SETI@Home]], which began in 1999, computes data averages more than 597 teraFLOPS.<ref>{{cite web |url=http://boincstats.com/en/stats/0/project/detail |title=SETI@Home Credit overview |publisher=BOINC |accessdate=April 15, 2012}}</ref>
| |
| | |
| * {{As of|2012|11}}, [[MilkyWay@Home]] computes at over 490 teraFLOPS, with a large amount of this work coming from GPUs.<ref>{{cite web|url=http://boincstats.com/en/stats/61/project/detail|title=MilkyWay@Home Credit overview|publisher=BOINC|accessdate=April 15, 2012}}</ref>
| |
| | |
| * [[Folding@home]] is sustaining over 9.6 native petaFLOPS as of October 2013<ref>{{cite web|url=http://fah-web.stanford.edu/cgi-bin/main.py?qtype=osstats |title=Client statistics by OS|date=October 4, 2013|publisher=Folding@Home|accessdate=October 4, 2013}}</ref> or 19.1 x86 petaFLOPS (x86 FLOPS are an approximate measurement of the speed of a calculation on an [[x86]]-based processor, different from native FLOPS<ref>{{cite web|url=http://folding.stanford.edu/home/faq/faq-flops|title=FLOP FAQ|date=July 1, 2013|publisher=Folding@Home|accessdate=October 19, 2013}}</ref>). It is the first computing project of any kind to cross the 1, 2, 3, 4, and 5 native petaFLOPS milestone. This level of performance is primarily enabled by the cumulative effort of a vast array of powerful [[Graphics processing unit|GPU]], [[PlayStation 3]] and [[Central processing unit|CPU]] units.<ref>{{cite news
| |
| | author = Staff
| |
| | title = Sony Computer Entertainment's Support for Folding@home Project on PlayStation3 Receives This Year's "Good Design Gold Award"
| |
| | url = http://www.scei.co.jp/corporate/release/081106de.html
| |
| | agency = Sony Computer Entertainment Inc.
| |
| | work = Sony Computer Entertainment Inc.
| |
| | publisher = Sony Computer Entertainment Inc.
| |
| | date = November 6, 2008
| |
| | accessdate = December 11, 2008
| |
| }}</ref>
| |
| | |
| * The entire [[BOINC]] network averages about 9.5 petaFLOPS {{As of|2013|03|19|alt=as of March 19, 2013}}.<ref>{{cite web |url=http://boincstats.com/en/stats/-1/project/detail |title=Credit overview |publisher=BOINC |accessdate=March 19, 2013}}</ref>
| |
| | |
| ===Future developments===
| |
| {{Further|Exascale computing}}
| |
| In 2008, [[James Bamford]]'s book ''[[The Shadow Factory]]'' reported that [[NSA]] told the [[The Pentagon|Pentagon]] it would need an exaflop computer by 2018.<ref>p339, [[Shadow Factory]], Bamford</ref>
| |
| | |
| Given the current speed of progress, [[supercomputer]]s are projected to reach 1 exaFLOPS (EFLOPS) in 2019.<ref>{{cite news |first=Patrick |last=Thibodeau |authorlink= |coauthors= |title=IBM breaks petaflop barrier |url=http://www.infoworld.com/article/08/06/10/IBM_breaks_petaflop_barrier_1.html |work=InfoWorld |publisher= |date=June 10, 2008 |accessdate= }}</ref> [[Cray, Inc.]] announced in December 2009 a plan to build a 1 EFLOPS supercomputer before 2020.<ref>{{cite web|url=http://eetimes.com/news/latest/showArticle.jhtml?articleID=222000288 |title=Cray studies exascale computing in Europe |publisher=Eetimes.com |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref> Erik P. DeBenedictis of [[Sandia National Laboratories]] theorizes that a zettaFLOPS (ZFLOPS) computer is required to accomplish full weather modeling of two week time span.<ref>{{cite book |chapter=Reversible logic for supercomputing |title=Proceedings of the 2nd conference on Computing frontiers |last=DeBenedictis |first=Erik P. |authorlink= |coauthors= |year=2005 |publisher= ACM Press|location= New York, NY|isbn=1-59593-019-1 |pages=391–402 |chapterurl=http://portal.acm.org/citation.cfm?id=1062325 }}</ref> Such systems might be built around 2030.<ref>{{cite news |first= |last= |authorlink= |coauthors= |title=IDF: Intel says Moore's Law holds until 2029 |url=http://www.h-online.com/newsticker/news/item/IDF-Intel-says-Moore-s-Law-holds-until-2029-734779.html |work=Heise Online |publisher= |date=April 4, 2008 |accessdate= }}</ref>
| |
| | |
| In India, [[ISRO]] and [[Indian Institute of Science]] have stated that they have planned to make a 132.8 EFLOPS supercomputer by 2017, 100 times faster than any [[supercomputer]] ever planned. They have estimated that the project would cost US $2 billion, which the state has budgeted.<ref>{{cite news | first=| last= | title= India to make World's Fastest Supercomputer|quote=|url=http://www.defencenews.in/defence-news-internal.asp?get=new&id=500 }}</ref>
| |
| | |
| ==Cost of computing==
| |
| | |
| ===Hardware costs===
| |
| | |
| The following is a list of examples of computers that demonstrates how drastically performance has increased and price has decreased. The "cost per GFLOPS" is the cost for a set of hardware that would theoretically operate at one billion floating-point operations per second. During the era when no single computing platform was able to achieve one GFLOPS, this table lists the total cost for multiple instances of a fast computing platform which speed sums to one GFLOPS. Otherwise, the least expensive computing platform able to achieve one GFLOPS is listed.
| |
| | |
| {| class="wikitable"
| |
| |-
| |
| ! Date
| |
| ! Approximate cost per GFLOPS
| |
| ! Approximate cost per GFLOPS inflation adjusted to 2013 US dollars<ref>http://data.bls.gov/cgi-bin/cpicalc.pl|publisher=US Government</ref>
| |
| ! Platform providing the lowest cost per GFLOPS
| |
| ! Comments
| |
| |-
| |
| | 1961
| |
| | US $1,100,000,000,000 ($1.1 trillion)
| |
| | US $8.3 trillion
| |
| | About 17 million [[IBM 1620]] units costing $64,000 each
| |
| | The {{Sic|hide=y|1620's}} multiplication operation takes 17.7 ms.<ref>{{cite web|url=http://ed-thelen.org/comp-hist/BRL61-ibm1401.html |title=IBM 1961 BRL Report |publisher=Ed-thelen.org |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| |-
| |
| | 1984
| |
| | $15,000,000
| |
| | $33,000,000
| |
| | [[Cray X-MP]]
| |
| |
| |
| |-
| |
| | 1997
| |
| | $30,000
| |
| | $42,000
| |
| | Two 16-processor [[Beowulf (computing)|Beowulf]] clusters with [[Pentium Pro]] microprocessors<ref>{{cite web|url=http://loki-www.lanl.gov/papers/sc97/ |title=Loki and Hyglac |publisher=Loki-www.lanl.gov |date=1997-07-13 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| |
| |
| |-
| |
| | {{sort|2000/04|April 2000}}
| |
| | $1,000
| |
| | $1,300
| |
| | [[Beowulf (computing)|Bunyip Beowulf cluster]] <!-- old link bad as of 2013-05-18 http://tsg.anu.edu.au/Projects/Beowulf/ -->
| |
| | Bunyip was the first sub-US-$1/MFLOPS computing technology. It won the Gordon Bell Prize in 2000.
| |
| |-
| |
| | {{sort|2000/05|May 2000}}
| |
| | $640
| |
| | $836
| |
| | [[Kentucky Linux Athlon Testbed|KLAT2]]
| |
| | KLAT2 was the first computing technology which scaled to large applications while staying under US-$1/MFLOPS.<ref>{{Cite journal|url=http://aggregate.org/KLAT2/ |title=Kentucky Linux Athlon Testbed 2 (KLAT2) |publisher=The Aggregate |date= |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| |-
| |
| | {{sort|2003/08|August 2003}}
| |
| | $82
| |
| | $100
| |
| | [http://aggregate.org/KASY0/ KASY0]
| |
| | KASY0 was the first sub-US-$100/GFLOPS computing technology.<ref>{{Cite journal|url=http://aggregate.org/KASY0/ |title=KASY0 |publisher=The Aggregate |date=2003-08-22 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| |-
| |
| | {{sort|2007/08|August 2007}}
| |
| | $48
| |
| | $52
| |
| | [http://www.calvin.edu/~adams/research/microwulf/ Microwulf]
| |
| | As of August 2007, this 26.25 GFLOPS "personal" Beowulf cluster can be built for $1256.<ref>{{cite web|url=http://replay.waybackmachine.org/20070912061302/http://www.calvin.edu/~adams/research/microwulf/ |title=Microwulf: A Personal, Portable Beowulf Cluster |publisher=Replay.waybackmachine.org |date=2007-09-12 |accessdate=2012-02-09|postscript=<!-- Bot inserted parameter. Either remove it or change its value to "." for the cite to end in a ".", as necessary. -->{{inconsistent citations}}}}</ref>
| |
| |-
| |
| | {{sort|2011/03|March 2011}}
| |
| | $1.80
| |
| | $1.80
| |
| | [http://hpu4science.org HPU4Science]
| |
| | This $30,000 cluster was built using only commercially available "gamer" grade hardware.<ref>Adam Stevenson, Yann Le Du, and Mariem El Afrit. "[http://arstechnica.com/science/news/2011/03/high-performance-computing-on-gamer-pcs-part-1-hardware.ars High-performance computing on gamer PCs]." ''Ars Technica''. March 31, 2011.</ref>
| |
| |-
| |
| | {{sort|2012/08|August 2012}}
| |
| | $0.75
| |
| | $0.73
| |
| | [http://www.amd.com/us/products/desktop/graphics/7000/7970/Pages/radeon-7970.aspx Quad AMD7970 GHz System]
| |
| | A quad AMD 7970 desktop computer reaching 16 TFlops of single-precision, 4 TFlops of single-precision computing performance. Total system cost was $3000; it was also built using only commercially available "gamer" grade hardware.{{Citation needed|date=April 2013}}
| |
| |-
| |
| | {{sort|2013/06|June 2013}}
| |
| | $0.22
| |
| | $0.22
| |
| | [http://www.scei.co.jp/corporate/release/130221a_e.html Sony Playstation 4]
| |
| | The Sony [[PlayStation 4]] is listed as having a peak performance of 1.84 TFLOPS, at a price of $400<ref>"[http://www.cnbc.com/id/100805004 Sony Sparks Price War With PS4 Priced at $399]." ''CNBC''. June 11, 2013.</ref>
| |
| |-
| |
| | {{sort|2013/11|November 2013}}
| |
| | $0.16
| |
| | $0.16
| |
| | [http://www.freezepage.com/1384601420XCIGYKCBKJ AMD Sempron 145 GeForce GTX 760 System]
| |
| | Built using commercially available parts, a system using one AMD Sempron 145 and three GeForce GTX 760 reaches a total of 6.771 TFLOPS for a total cost of $1090.66.<ref>http://www.freezepage.com/1384601420XCIGYKCBKJ</ref>
| |
| |
| |
| |-
| |
| | {{sort|2013/12|December 2013}}
| |
| | $0.12
| |
| | $0.12
| |
| | [http://www.freezepage.com/1387480124PSLSILVCMJ Pentium G550 R9 290 System]
| |
| | Built using commercially available parts. Pentium G550 & AMD R9 290 tops out at 4.848 TFLOPS grand total of $681.84 USD. <ref>http://www.freezepage.com/1387480124PSLSILVCMJ</ref>
| |
| |}
| |
| | |
| <!-- These were removed because they only cited the price of the processor; this table is supposed to compare the total cost of the machine. -----------
| |
| | {{sort|2007, March|March 2007}}
| |
| | $0.42
| |
| | [[Ambric]] AM2045<ref>{{cite journal|last=Halfill|first=Tom R.|date=October 10, 2006|title=Ambric's New Parallel Processor|journal=Microprocessor Report|publisher=Reed Electronics Group|pages=1–9|url=http://www.ambric.com/pdf/MPR_Ambric_Article_10-06_204101.pdf|accessdate=July 8, 2008|format=|archiveurl = http://web.archive.org/web/20080627111128/http%3A//www.ambric.com/pdf/MPR_Ambric_Article_10-06_204101.pdf |archivedate = June 27, 2008|deadurl=yes}}</ref>
| |
| |
| |
| |-
| |
| | {{sort|2009, September|September 2009}}
| |
| | $0.13 (single precision)
| |
| | [[ATI Technologies|ATI]] [[Evergreen (GPU family)|Radeon R800]]<ref>{{cite news|url=http://www.brightsideofnews.com/news/2009/9/29/the-fastest-ati-5870-card-achieves-3tflops!.aspx|title=The fastest ATI 5870 card achieves 3TFLOPS!|author=Valich, Theo|date=September 29, 2009|publisher=Bright Side of News|accessdate=September 29, 2009}}</ref>
| |
| |The first high-performance 40 nm [[Graphics processing unit|GPU]] from ATI. It can reach speeds of 3.04 TFLOPS when running at 950 MHz. Price per GFLOPS is slightly inaccurate as it is single precision and includes only the cost of the card.
| |
| |-
| |
| | {{sort|2011, March|March 2011}}
| |
| | $0.13
| |
| | [[Advanced Micro Devices|AMD]] [[Comparison of AMD graphics processing units#Northern Islands .28HD 6xxx.29 series|Radeon HD 6990]] [[Overclocking|Overclocked]]<ref>http://www.hardocp.com/images/articles/1299536835FpEmksdSXb_1_3_l.gif</ref>
| |
| |Floating-point performance (peak): 5.40 TFLOPS. Price: $699.
| |
| |}
| |
| |-
| |
| | {{sort|2013/04|April 2013}}
| |
| | $0.12
| |
| | $0.12
| |
| | [http://www.amd.com/us/products/desktop/graphics/7000/7990/pages/radeon-7990.aspx#2 AMD Radeon HD 7990]
| |
| | The AMD Radeon HD 7990 is a GPU with single precision computing performance reaching 8.2 TFlops. It was released on 24 April, 2013 with a price point of $1000.
| |
| ---->
| |
| | |
| <!--* 2006, February: about $1 per GFLOPS in ATI PC add-in graphics card (X1900 architecture) — these figures are disputed as they refer to highly parallelized GPU power-->
| |
| <!-- The source does not state whether FLOPS is SP or DP, which is misleading: * 2007, October: about $0.20 per GFLOPS with the cheapest retail [[Sony PS3]] console, at US$400, that runs at a claimed 2 teraFLOPS; these figures represent the processing power of the [[Graphics processing unit|GPU]]. The seven [[Central processing unit|CPU]]s run collectively at a lower 218 GFLOPS.<ref>{{cite news|url=http://news.bbc.co.uk/2/hi/technology/4554025.stm|title=Sony shows off new PlayStation 3|last=Hermida |first=Alfred |date=May 17, 2005|publisher=BBC News|accessdate=July 8, 2008}}</ref> -->
| |
| <!--* 2008, June/July: ~20c (€) per GFLOPS with AMD's HD4870 GPU. These figures are disputed as they refer to highly parallelized GPU power-->
| |
| The trend toward placing ever more transistors inexpensively on an integrated circuit follows [[Moore's law]]. This trend explains the rising speed and falling cost of computer processing.
| |
| | |
| ===Operation costs===
| |
| | |
| In energy cost, according to the [[Green500]] list, {{as of|2011|06|lc=on}} the most efficient [[TOP500]] supercomputer runs at 2097.19 [[FLOPS per watt|MFLOPS per watt]]. This translates to an energy requirement of 0.477 [[watt]]s per [[GFLOPS]], however this energy requirement will be much greater for less efficient supercomputers.
| |
| | |
| Hardware costs for low cost supercomputers may be less significant than energy costs when running continuously for several years.
| |
| | |
| == Floating-point operation and integer operation ==
| |
| | |
| FLOPS measures the computing ability of a computer. An example of a floating-point operation is the calculation of mathematical equations; as such, FLOPS is a useful measure of supercomputer performance. [[Million instructions per second#Million instructions per second|MIPS]] is used to measure the integer performance of a computer. Examples of integer operation include data movement (A to B) or value testing (If A = B, then C). MIPS as a performance benchmark is adequate for the computer when it is used in database query, word processing, spreadsheets, or to run multiple virtual operating systems.<ref>[http://www.dspguide.com/ch28/4.htm Fixed versus floating point.] Retrieved on December 25, 2009.</ref><ref>[http://www.dspguide.com/ch28/1.htm Data manipulation and math calculation.] Retrieved on December 25, 2009.</ref> Frank H. McMahon, of the Lawrence Livermore National Laboratory, invented the terms FLOPS and MFLOPS (megaFLOPS) so that he could compare the so-called supercomputers of the day by the number of floating-point calculations they performed per second. This was much better than using the prevalent MIPS to compare computers as this statistic usually had little bearing on the arithmetic capability of the machine.
| |
| | |
| === Fixed-point (integers) ===
| |
| | |
| These designations refer to the [[Computer number format|format]] used to store and manipulate numeric representations of data without using a decimal point (it is 'fixed' at the end of the number). Fixed-point are designed to represent and manipulate [[integers]] – positive and negative whole numbers; for example, 16 bits, yielding up to 65,536 (2<sup>16</sup>) possible bit patterns that typically represent the whole numbers from −32768 to +32767.<ref>[http://www.dspguide.com/ch4/2.htm Integer] Retrieved on December 25, 2009.</ref>
| |
| | |
| === Floating-point (real numbers) ===
| |
| | |
| This is needed for very large or very small [[real number]]s, or numbers requiring the use of a decimal point (such as [[pi]] and other [[Irrational number|irrational]] values). The encoding scheme used by the processor for floating-point numbers is more complicated than for fixed-point. Floating-point representation is similar to scientific notation, except everything is carried out in base two, rather than base ten. The encoding scheme stores the sign, the [[exponent]] (in base two for Cray and [[IEEE floating point]] formats, or base 16 for [[IBM Floating Point Architecture]]) and the [[Significand|mantissa]] (number after the decimal point). While several similar formats are in use, the most common is [[IEEE 754-1985|ANSI/IEEE Std. 754-1985]]. This standard defines the format for 32-bit numbers called ''single precision'', as well as 64-bit numbers called ''double precision'' and longer numbers called ''extended precision'' (used for intermediate results). Floating-point representations can support a much wider range of values than fixed-point, with the ability to represent very small numbers and very large numbers.<ref>[http://www.dspguide.com/ch4/3.htm Floating Point] Retrieved on December 25, 2009.</ref>
| |
| | |
| === Dynamic range and precision ===
| |
| | |
| The exponentiation inherent in floating-point computation assures a much larger dynamic range – the largest and smallest numbers that can be represented – which is especially important when processing data sets which are extremely large or where the range may be unpredictable. As such, floating-point processors are ideally suited for computationally intensive applications.<ref>[http://www.analog.com/en/embedded-processing-dsp/content/Fixed-Point_vs_Floating-Point_DSP/fca.html Summary: Fixed-point (integer) vs floating-point] Retrieved on December 25, 2009.</ref>
| |
| | |
| == See also ==
| |
| {{Portal|Computer Science}}
| |
| | |
| * [[Gordon Bell Prize]]
| |
| * [[Orders of magnitude (computing)]]
| |
| | |
| {{clear}}
| |
| | |
| ==References==
| |
| {{Reflist|30em|refs=
| |
| <ref name="Petaflops">{{cite web|url=http://www.fujitsu.com/global/news/pr/archives/month/2011/20111102-02.html |title='K computer' Achieves Goal of 10 Petaflops |publisher=Fujitsu.com |date= |accessdate=2012-02-09}}</ref>
| |
| }}
| |
| | |
| ==External links==
| |
| *[http://einstein.phys.uwm.edu/server_status.php Current Einstein@Home benchmark]
| |
| *[http://boincstats.com/en/stats/-1/project/detail BOINC projects global benchmark]
| |
| *[http://mersenne.org/primenet/ Current GIMPS throughput]
| |
| *[http://www.top500.org Top500.org]
| |
| *[http://www.LinuxHPC.org LinuxHPC.org] Linux High Performance Computing and Clustering Portal
| |
| *[http://www.WinHPC.org WinHPC.org] Windows High Performance Computing and Clustering Portal
| |
| *[http://svn.oscar.openclustergroup.org/php/clusters_register.php?sort=rpeak Oscar Linux-cluster ranking list by CPUs/types and respective FLOPS]
| |
| *[http://www.mosis.org/forms/mosis_forms/ECCN_CTP_Computation.pdf Information on how to calculate "Composite Theoretical Performance" (CTP)]
| |
| *[http://investors.cray.com/phoenix.zhtml?c=98390&p=irol-newsArticle&ID=873357&highlight= Information on the Oak Ridge National Laboratory Cray XT system.]
| |
| *[http://www.perceus.org/portal/ Infiscale Cluster Portal – Free GPL HPC]
| |
| *[http://www.roylongbottom.org.uk/index.htm Source code, pre-compiled versions and results for PCs] – [[Linpack]], Livermore Loops, [[Whetstone (benchmark)|Whetstone]] MFLOPS
| |
| *[http://www.roylongbottom.org.uk/cpuspeed.htm PC CPU Performance Comparisons %MFLOPS/MHz – CPU, Caches and RAM]
| |
| *[http://www.intel.com/support/processors/xeon/sb/CS-020863.htm Xeon export compliance metrics], including GFLOPS
| |
| *[http://www.hpcwire.com/features/IBM-Brings-NVIDIA-GPUs-Onboard-94190024.html IBM Brings NVIDIA Tesla GPUs Onboard (May 2010)]
| |
| | |
| {{DEFAULTSORT:Flops}}
| |
| [[Category:Computer benchmarks]]
| |
| [[Category:Units of frequency]]
| |