Talk:FLOPS

message: The AMD section does not include 3DNow! which was AMD's equivalent (and then some) of Intel's MMX for floating point acceleration.  I believe they also had the equivalent of an x87 unit in their earlier processors?
I'm not sure how necessary the table truly is to the article however.  — Preceding unsigned comment added by 75.138.33.10 (talk) 02:01, 14 January 2024 (UTC)
thread_title:  Processor table 

message: The records section has some significant errors in it. The section itself is completely speculative, as no actual BlueGene/P systems have been deployed yet. Currently, no computational system operates at sustained speeds in excess of a single petaflop. The IBM press release being used is not objective, and it should not be stated as a record until the speed is demonstrated publicly, or through an independent entity such as TOP500.
Really, the whole section needs to be cleaned up, as the SX-9 has not public benchmarks available either.
In fact, if one wants to speculate about the fastest computers, it would be perhaps more useful to include a discussion of the NSF Track 2 systems, as well as the proposed Track 1 system (which is specifically being designed to operate in excess of one petaflop, sustained)
The currently operational track 2 system RANGER is operating at approximately half a petaflop, putting it around the current speeds of the BlueGene systems that have been deployed.
I have a comment on the records section, in regards to this paragraph:
"As of 2008, the fastest PC processors (quad-core) perform over 51 GFLOPS(QX9775)[13]. GPUs in PCs are considerably more powerful in pure FLOPS. For example, in the GeForce 8 Series the nVidia 8800 Ultra performs around 576 GFLOPS on 128 Processing elements. This equates to around 4.5 GFLOPS per element, compared with 2.75 per core for the Blue Gene/L. It should be noted that the 8800 series performs only single precision calculations, and that while GPUs are highly efficient at calculations they are not as flexible as a general purpose CPU."
If you want to show that graphics cards can perform considerably more flops, why not compare to the ATI Radeon 4870X2, which can do 2.4 teraflops?  That's over four times faster than the 8800 ultra that's listed.  —Preceding unsigned comment added by 128.205.179.184 (talk) 20:33, 14 August 2008 (UTC)
thread_title:  Records Section 

message: Why do people write FLOPS and MIPS rather than flops and mips? I cannot think of a good reason for the capitals. And besides, people write mph (miles per hour) and dpi (dots per inch) rather than MPH and DPI. I rewrote the article with flops and it doesn't look bad, I think. Is there a reason why I shouldn't move this article to Flops? —Herbee 22:09, 2004 May 22 (UTC)
: FLOPS is the correct abbreviation, flops is not a word. Non-technical people usually write FLOPS as flops usually out of ignorance of what the abbreviation actually means. --Gunter 18:18, 8 Jan 2005 (UTC)
replies: text: It is FLOPS in Computer Architecture by Hennessy and Patterson and flop/s or Flop/s or FLOPS in Sourcebook of Parallel Computing by Dongarra et al. Personally I think it should be FLOPS, but there is no consistency in respected publications. By the way, it is MPH in my car. --Koobas 17:15, 7 August 2006 (UTC)
thread_title:  Question 

message: As a mathematician, the use of the term 'metric' makes me uneasy. Isn't there a better, less jargon-y, alternative: 'measure' perhaps? mat_x 19:46, 31 Dec 2004 (UTC)
thread_title: Metric

message: I recently removed the following:
The computers that generated Lord of the Rings characters and places - Gollum, the Balrog, and Middle Earth - are now available for hire, for example. The cluster of 1,008 computers in New Zealand can be rented on-demand, on a per hour, per processor basis.
Already the supercomputer is being used to design a super yacht and test gene sequencing algorithms.
The first paragraph is not related to FLOPS and is somewhat abrupt in context.
The second paragraph is ambiguous to which supercomputer it is referring to, and probably irrelevent in any case.
--Zdude255 21:56, 6 Apr 2005 (UTC)
thread_title:  Removal of Irrelevant and Ambiguous Material 

message: Removed from the article:
:Nvidia work out performance by adding pixel shader and vertex shader performance together (in the PS3s case this is 1.8 TFLOPs). ATI work out performance by taking the average performance of the two shader types (quoted at 0.9 TFLOPs), and so if the ATI performance was taken by the same method as Nvidia then the performance would be the same. And so the total performance of the Xbox 360 would be around the 2 TFLOPs mark too. However as it stands Microsoft have released figures based on ATI's figures (1 TFLOPs).
This seems to be a marchitecture-based dicussion. Can we let this be fought out on the games console article talk pages, please? This article now, in any case, compares manufacturer-announced FLOPs in each case: marchitecture vs. marchitecture. More in the article. -- Karada 12:30, 23 May 2005 (UTC)
thread_title:  NVIDIA vs. VIA 

message: :Humans are even worse floating-point processors. If it takes a person a quarter of an hour to carry out a pencil-and-paper long division problem with 10 significant digits, that person would be calculating in the milliFLOPS range. Bear in mind, however, that a purely mathematical test may not truly measure a human's FLOPS, as a human is also processing smells, sounds, touch, sight and motor coordination. This takes an average human's FLOPS up to an estimated 10 quadrillion FLOPS (roughly 10 PFLOPS). 
Wasn't that in MIPS? As the article says:
:We might take a rough estimate and say it is handling 10 quadrillion instructions per second, but it really is hard to say.
I belive we should assume that it's about 10 GMIPS, not 10 PFLOPS.
--83.11.55.87 17:10, 14 February 2006 (UTC)
replies: text: Based on some rough math using OpenWorm as a reference point, modeling the human brain will take in excess of 63.8 Exaflops (1018).  This could be wildly under-estimated as I may not be accounting for the 100 Trillion Synapses.  If we are to believe the microtubular computing theory, then this figure could rise to 1024 . 92.25.228.128 (talk) 15:31, 4 May 2012 (UTC)
thread_title: Human mind in FLOPS?

message: "Pocket calculators are at the other end of the performance spectrum. Each calculation request to a typical calculator requires only a single operation..."
How is it possible to compute something in one operation? It first has to store the first operand that's typed in before even starting to compute. Or am I misunderstanding the meaning of the word "operation."83.118.38.37 19:28, 25 August 2006 (UTC)
replies: text: Gave it some second thought and I see wat is meant now.83.118.38.37 03:18, 26 August 2006 (UTC)
replies: text: It's the difference between "operations" and "instructions"... the device may process a few hundreds of instructions per second, but only manage ten or twenty operations. Or in the case of an everyday mid-level scientific calculator (say a $20 Casio 85fx or the like), maybe a couple of KIPS but only 50 or so FLOPS... as seen when issuing an instruction like "!69" (it's an integer operation, but the calculator will treat all numbers as fixed-precision floats, so...) which involves 68 seperate multiplication operations, each involving a good number of seperate instructions, and needs more than a second to calculate (blanking the display whilst it works). Or much longer if power is low (they seem to work asynchronously and on the basis of how much current is available - not an issue if the user is just doing simple sums and it's more important to keep the LCD contrast high, but the scientific operations can become quite drawn-out). But it's no bad thing; it doesn't need to go any faster, and it makes the batteries last an awful long time. 193.63.174.10 (talk) 12:31, 17 November 2010 (UTC)
thread_title: Computing in One Operation

message: In the article it says that the character "data" in Star Trek was as fast as 60 trillion operations per second or "60 TIPS". My question is, what is this "TIPS" - word? Should it not be properly explained in the article? Also it would be cool if someone with knowledge about computers wrote something about how fast that would be in comparison to todays super computers. --Mailerdaemon 13:12, 15 November 2006 (UTC)
replies: text: The Trek writers' policy is actually to prevent such comparisons, because they know their imagination will probably be hilariously off the mark at the supposed time of events happening, or even long before. "TIPS" could be "tera", or it could be some other unit entirely. Compared with "Quads" of storage - the T could be "Trios" or somesuch. A completely made-up measurement. Anyhow, regardless of the deliberate neutering of such attempts, coming up with comparisons between our real-world hardware (hard enough to benchmark at the best of times) and completely fictional and poorly defined stuff stated to be first used after our likely lifespans isn't really of any use. My 2100mhz, dual core, high cycle efficiency, high ram, hard disk equipped, dual hi-rez full colour monitor workstation is approximately 1000x better in all meaningful stats than my first "proper" (non-"toy") computer. For the majority of stuff I do with it, it's not really more than 3 or 4x better, and for some things, it's about the same or maybe worse. Power doesn't necessarily imbue utility. 193.63.174.10 (talk) 13:07, 17 November 2010 (UTC)
replies: text: Actually in the show Data says literally "60 trillion operations per second". His storage capacity is also literally stated as "800 quadrillion bits". --Colin Barrett (talk) 18:07, 9 August 2011 (UTC)
thread_title:  Data 

message: The article stats the following: "a purely mathematical test will not truly measure a human's FLOPS, as a human is also processing thoughts, consciousness, smells, sounds, touch, sight and motor coordination."  Since the definition of a FLOP is floating point operation per second, I fail to see how thought processing, consciousness, smells, sounds, touch etc. have anything to do with FLOPS.  Unless someone can give me a reason for not doing so, I will delete this phrase after a couple days. Epachamo 00:36, 8 April 2007 (UTC)
replies: text: The fact that we have many background processes and cannot turn off these background processes is one reason WHY we cannot do many FLOPS, but does not change the fact that we CAN'T do many FLOPS.  If FLOPS are your measuring stick, then we stink.  However, we rock computers at image processing still ;) (and swimming)Epachamo 01:42, 24 April 2007 (UTC)
thread_title:  Human FLOPS 

message: *single-purpose hardware can never be included in an honest FLOPS figure.
if you include MDGRAPE-3 then other single-purpose hardware must be included also; also debatable if the new GPUs are really single-purpose, as they can perform graphics rendering and Folding. Also, please sign your comments in future, this is Wikipedia policy.Jaganath 09:28, 8 May 2007 (UTC)
thread_title:  flops 

message: Does anyone else think the records section should be in order of flops? 
Craig Mayhew 16:33, 3 July 2007 (UTC)
thread_title:  Records 

message: Shouldn't the article differencieate between double precious and single precision floating point operations? A processor designed specifically to perform single precision operations may not perform so well with operations with double precision and vice versa. Adding a section explaining the difference between the two may also clear up some common misconceptions, such as only the FLOPS count being important. Rilak (talk) 07:31, 9 December 2007 (UTC)
thread_title:  Precision? 

message: In the cost of computing section, the calculation assumes continuous 135 watt consumption for the PS3 console. Even when in operation and under load, it is unlikely that the console continuously consumes 135 watts, so the claim that it would consume $118 worth of electricity at average US electricity prices is misleading.  —Preceding unsigned comment added by 68.145.105.18 (talk) 16:28, 22 April 2008 (UTC)
thread_title:  Cost of computing 

message: It is a bit silly that the side panel goes up to the unit of xeraflop, given that 1 xeraflop is about a billion times more that the sum of the entire computing power on Earth. It is not particularly useful to include units which have not yet found a use. Even statements about hypothetical computing power in the future are much clear when expressed in terms of units that are actually used now. For example "The supercomputers of 2020 may be a thousand petaflops" gets the message across better than "The supercomputers of 2020 may be one exaflop", since the exaflop unit has no real reason to be used yet. Elroch (talk) 11:51, 13 May 2008 (UTC)
replies: text: This argument would apply to Yottaflop and the measurements are simply there to show the path of growth -- even if we won't exist to enjoy it. Lordvolton (talk) 15:26, 24 May 2008 (UTC)
replies: text: Never mind that we've already easily managed such a magnitude increase of computing capacity once over the past century? These units will be in use at some point, possibly sooner than might be easily imagined, so why not use them? Furthermore they're simply part of the normal SI range of exponential prefixes, it's not like some bored computer engineer has dreamt them up off his own back. Same as going in the other direction down to micro, nano, pico, femtoFLOPs (etc) if for some reason an exceptionally slow computing device (but maybe one that did an awful lot with that one operation!) was to be built or discovered... 193.63.174.10 (talk) 13:16, 17 November 2010 (UTC)
thread_title:  Silly units 

message: Supercomputer sets petaflop pace http://news.bbc.co.uk/1/hi/technology/7443557.stm  —Preceding unsigned comment added by 99.247.28.157 (talk) 18:19, 9 June 2008 (UTC)
thread_title:  IBM Roadrunner 

message: -- has all sorts of information comparing the first list to the 30th and lists all sorts of records that were broken Altonbr (talk) 15:34, 10 June 2008 (UTC)
thread_title:  Excellent citation paper 

message: Under "Cost of Computing" it is stated that IBM Roadrunner costs $0.13 per GFLOPS. 
The cost is actually closer to $130 per GFLOPS, if I am not mistaken.
:: Cost to build Roadrunner: $133 million USD
:: Roadrunner performance: 1.026 petaFLOPS (1026000 GFLOPS)
:: $133,000,000 / 1026000 = $129.6296 per GFLOPS
Perhaps I am wrong, someone please double check the math. Remain nameless (talk) 14:19, 19 July 2008 (UTC)
thread_title:  Incorrect $/GFLOP for IBM Roadrunner? 

message: This section of the article has me confused. I don't know whether the prices represent the cost of individual components, specific machines or anything else for that matter. Could someone please clear this up by explaining what the prices are linked to. I have also marked it as confusing on the article. Supersword (talk) 23:20, 16 November 2008 (UTC)
replies: text: I've reworked that section a bit; I think I consider it to be clear enough now, so I'm (tentatively) removing the tag. - Reinderientalk/contribs 21:39, 28 February 2009 (UTC)
thread_title:  'Cost of Computing' section is confusing 

message: "As of 2008, the fastest PC processors (quad-core) perform over 70 GFLOPS"
I have credibility issues with this.
Given a speed of 3.2GHz with 4 cores and completing one operation per cycle this gives 12.8 GFLOPS. Even assuming perfect hyperthreading that doubles the effective number of cores this is still a factor of 3 short.
The reference given in the quote goes to a website that shows a graph of CPU speed giving 70 GFlops for a top spec processor but is this believable?
Mtpaley (talk) 23:03, 16 August 2009 (UTC)
replies: text: You have to calculate the peak performance of an Intel Core2/i7 like that: SSE2 => 2 doubles in each vector; 2 different ports and 2 different execution units with a throughput of one µop for floating point addition and multiplication => one packed double addition and multiplication in one clock cycle. Hyperthreading shares the execution units and other resources, resulting not in a higher FLOPS count. So you get 4 DP FLOP per core and clock cycle. This results in FLOPS = frequency*(# of cores)*4 = 79.9 GFLOPS for a six core i7-980X.  —Preceding unsigned comment added by 88.67.216.116 (talk) 19:51, 23 April 2010 (UTC)
thread_title:  PC Speed 

message: That blasted Xera- prefix showed up again.  I nuked it.  <soapbox> Ever since the Tera- prefix the standards people at SI have based the new prefix on Greek or Latin (mostly Greek) terms relating to the number of 000s.  The next one not yet defined is 9 sets of 000s.  So if Greek is used again for nine, εννέα or ennéa, we might have enyaFLOPS, which is cool if you like her music.  Or if Latin, it's either nove or nona.  I say go with Latin, combine the two forms, and we get NovaFLOPS, which sounds pimp.  Either way, it's moot, because SI has not established a 1027 prefix yet.  At all.  My personal best guess is that someone's signature on the Starcraft forums (I'm not making this part up) who even acknowledged that it's a bogus word, got propagated into some crease of the public consciousness and found it's way here.  It's still wrong.  I've seen people talking on here mention that a Google of "xeraflops" gets lots of hits, but a search of "xera" with "prefix" gets only a few thousand and most on the first page do not have any relation to numbers or SI. </soapbox>  Still doesn't exist.  Thank you.  -:-   AlpinWolf   -:- 06:11, 8 January 2010 (UTC)
thread_title:  Aw, not this again... 

message: There should be a list of current processors (Intel Core i7, Athlon 64, Cell, etc.) and their computing power in this article, shouldn't it? --bender235 (talk) 15:53, 4 February 2010 (UTC)
replies: text: Presactly. It's somewhat glaring by its absence - and the linked sites with supposed benchmark results on are baffling, lack easy to read summaries and are practically useless unless you're really wanting to see which small variant of a processor is marginally better at one element of an obscure test versus another slightly different one. They're complicated enough that I'm not even 100% sure what they show, and I'm certainly not motivated enough to pull all the data off them, learn what it means and reprocess it. A simple table, maybe even line/bar chart (logarithmically scaled?) showing fastest desktop CPU in terms of FLOPS measured by a widely regarded benchmark that spits out that figure (with all floating point accelerating features available and turned on) should do. Maybe have additional lines/bars for AMD vs Intel vs..., or premium vs budget lines... whatever. Extra data of interest could be FLOPS/Hz, and FLOPS/retail cost (everyday processors appear to be the missing link in the existing cost-per-flop table, it goes straight from huge mainframes into desktop-machine-based clusters and then to GPUs (without the cost of the necessarily attached other hardware!). Even though they obviously wouldn't be the fastest, cheapest or simplest way of getting your supercomputing oomph, it would demonstrate what this power means in a way that the lay user could understand - relating it to the device that they're using to access the article. Information on its own without understanding is effectively meaningless (and not having the information at all is worse). 193.63.174.10 (talk) 13:42, 17 November 2010 (UTC)
thread_title:  List of current processors 

message: For example, does a FLOP involve one or two floating point numbers?
Assuming two, is it the addition of two FP numbers?
Is it a multiplication? Division? Subtraction? If this was answered, I apologize, that I didn't see it.  —Preceding unsigned comment added by BobEnyart (talk • contribs) 16:38, 1 June 2010 (UTC)
replies: text: I've tried to answer it higher in the page, but I didn't know where to add the information on the main page, plus it looked like original research to meYitscar (talk) 14:02, 1 July 2010 (UTC)
replies: text: It's probably not clarified because it strongly depends on the context. In digital signal processing a flop often refers to a multiplication plus an addition because it's a common operation in filtering. Note that often some special architectures are used here  using dedicated chips for the cpu consuming operations (like wired multiplications) introducing different FLOPS "levels" on a same board. In classrooms additions and substractions are often ignored and only multiplications and/or divisions are counted. Is there an official definition of "FLoating point OPeration"?(MaenINoldo (talk) 08:33, 12 October 2010 (UTC)
replies: text: As above, and as well as I know, it is one addition, subtraction, multiplication, or division. For comparable benchmarks, the ratios of those operations will be about the same, such that the numbers are comparable. Gah4 (talk) 02:02, 18 July 2018 (UTC)
thread_title:  Article describes what a floating point number is, but does is say what an op is? 

message: The Radeon HD 5970 has got 2*320 dp-capable ALUs running at 725 MHz. Each of them can calculate one dp FMA (fused multiply add) per cycle. So the computing power is 2*320*725*2 MFLOPS = 928 GFLOPS and not 1.09 TFLOPS (citation of reference no. 38).
(87.180.223.105 (talk) 19:10, 14 October 2010 (UTC)
thread_title:  Double precision (dp) FLOPS of Radeon HD 5970 

message: http://news.yahoo.com/s/afp/20101028/tc_afp/chinatechnologyitworld
Accordion to this news story a new computer in china is taking that #1 spot. Good idea to keep an eye out for updates worth mentioning in the article.Donhoraldo (talk) 13:10, 28 October 2010 (UTC)
thread_title:  New record 

message: Any objections to me setting up auto-archive on this page? —me_and 14:34, 17 November 2010 (UTC)
thread_title:  Auto archive 

message: bitcoinwatch.com/ calculates PFLOPS of bitcoin network as: take number of Hashes/second (Terahashes/s of SHA256) and multiply by 12700 to get a "Single-precision FLOPS estimate". One hash calculation is considered as 6350 32-bit integer operations, and each integer operation is considered equal to two single-precision flops. Source of constants is: http://forum.bitcoin.org/index.php?topic=4689.0 (with reference to bincoinwatch's admin). Actual bitcoin mining contains no (or almost no) floating-point calculations.
: Thanks for constants! Some refs and quotes for such calculations and about their incorrectness: `a5b (talk) 03:38, 17 November 2013 (UTC)
thread_title:  Bitcoin "FLOPS" computation on bitcoinwatch 

message: While the statement is indeed sourced, it seems strange that India will accomplish 100x what supercomputer leaders plan in the same timeframe. If this is indeed the case, there should be more sources available then the single article that has been provided. Moreover, http://www.hpcwire.com/hpcwire/2012-01-04/india_aims_to_double_r_d_spending_for_science.html specifically mentions that there are dubious articles surrounding the matter. This source can be found on the wikipedia page Supercomputing in India.  —(shaun) Preceding unsigned comment added by 71.53.29.50 (talk) 00:16, 3 May 2012 (UTC)
replies: text: Lots of people have planned lots of things. And per WP:Crystal I zapped the futuristic part. Plans can fail. History2007 (talk) 17:50, 28 May 2012 (UTC)
thread_title:  ISRO >100 EFlops by 2017 is highly unlikely 

message: I removed the following section:
It is also important to consider fixed and floating-point formats in the context of precision – the size of the gaps between numbers. Every time a processor generates a new number via a mathematical calculation, that number must be rounded to the nearest value that can be stored via the format in use. Rounding and/or truncating numbers during processing naturally yields quantization error or ‘noise’ - the deviation between actual values and quantized values. Since the gaps between adjacent numbers can be much larger with fixed-point processing when compared to floating-point processing, round-off error can be much more pronounced. As such, floating-point processing yields much greater precision than fixed-point processing, distinguishing floating-point processors as the ideal CPU when computing accuracy is a critical requirement.
The above paragraph is totally wrong, even though it is a direct quote from Summary: Fixed-point (integer) vs floating-point.  The reason that article makes that claim there, but it is wrong when quoted here, is because they are comparing their 16 bit Fixed Point product to their 32 bit Floating Point product.  Actually their marketing is being a little bit deceptive in this regard.  Given the same number of bits, Floating Point has greater dynamic range but less Percision when compared to Fixed Point.
I am also concerned about the copyright issues, large chucks of that article "Fixed-point (integer) vs floating-point"  have been copied and pasted directly into this wiki article.  OldCodger2 (talk) 22:07, 22 June 2012 (UTC)
thread_title:  removed incorrect info about percision of floats vs fixed point - also copyright concerns 

message: :GFLOPS = chassis * \frac{nodes}{chassis} * \frac{sockets}{node} * \frac{cores}{socket} * GHz * FLOPS
Really?  GFLOPS = (something) × FLOPS?  Uh, yes, GFLOPS = (1/1000) × FLOPS, always, by definition.
First, the author of the original reference at Dell was sloppy in using "FLOPs" as a plural, which is so easily confused with "FLOPS", a rate, differentiated only by capitalization; and then second, a Wikipedia author copied the original formula incompletely, and didn't notice the glaring inconsistency which that left.  :(
It would be easy enough to correct the units and missing terms, but that would still leave a formula which (1) is overly-simplistic, as it doesn't consider threads, pipelines, functional units, or any other hardware details beyond mass-market home PC advertising; (2) doesn't consider asymmetric or hybrid mixed-processor machines, or even MPP machines with non-identical nodes; and (3) at best only calculates an absolute upper limit of FLOPS or GFLOPS, which can only ever be achieved with a very limited optimum instruction sequence, and then only for an ultra-brief time while the FP inputs can be taken from CPU registers.  In short, we'll get a significantly more complicated formula to calculate a result that borders on useless.
This brief section was only added to the article within the past week or so.  Is there general consensus that it needs to be a part of this article?  And does it need to be the lead section of the article?
98.218.86.55 (talk) 23:47, 8 October 2012 (UTC)
thread_title:  "Computing" [non-]forumla 

message: The explanation about fixed point arithmetic in this article is not very good in my opinion, and it is also partially wrong. The actual article on the subject is much better. The same goes for floating point arithmetic. Since this is explained better in other places on wikipedia, I think this section should be deleted. Amaurea (talk) 16:23, 20 March 2013 (UTC)
thread_title:  Fixed and floating point section 

message: The equation for calculating theoretical FLOPS is for the number of logical cores, not physical cores (unless 1 logical per physical). The numbers Intel provides supports this statement. I will leave it to the editors to decide how to incorporate this information into the article. http://www.intel.com/support/processors/sb/CS-032814.htm 76.198.38.250 (talk) 20:45, 23 June 2013 (UTC)
thread_title: Calculating Flops

message: Reference number 2 is no longer valid. 76.198.38.250 (talk) 06:29, 30 June 2013 (UTC)
thread_title: Reference Number 2

message: In computing, FLOPS (also flops, for FLoating-point Operations Per Second, or flop/s (< this last choice can't be correct, as the / sign means per, so it basically says FLoating-point Operations Per per Second. Makes no sense, on the same level as ATM machine or PIN number.) is a measure of computer performance.
My comment is in (). — Preceding unsigned comment added by 153.25.178.61 (talk) 02:22, 2 July 2013 (UTC)
thread_title:  Intro section 

message: The PS3 is listed at the same 1.84TFLOP, yet costs $250. Plenty of machines costing less than $750 also provide more than 4TFLOP (using cheap processor+ AMD 7970 GHz Ed), so the PS4 does not belong there at all, it is neither an average nor the best performance for price.  — Preceding unsigned comment added by 60.43.54.2 (talk) 15:02, 20 October 2013 (UTC)
thread_title:  Incorrect data in cost per flop 

message: I was wondering what a typical computer, device or tablet out there in the wild is capable of performing now. It would appear that a high-end smartphone should outperform a Cray X-MP supercomputer (from the 1980s) within the next few months, if not already... Using Linpack, a good speed is 200 MFLOPS on Android when I wrote this. Using a native app and multithreading, some ARM CPUS have surpassed the 400 to 800 MFLOPS of a Cray X-MP. Many smartphones outperform the Cray 1 already at floating point. It would be interesting to compare their I/O speed and storage, which for the Cray XM-P were based on solid state drives, 1.2 GB hard drive systems, and streaming mag tapes. I wonder which is faster: Bluetooth or mag tape? Near-field communication or modems? I like to saw logs! (talk) 09:01, 28 May 2014 (UTC)
thread_title:  Smartphone FLOPS... now surpass a supercomputer 

message: The section Hardware costs includes a table of milestones, and a heading paragraph which doesn't match the table.  The heading claims that “the least expensive computing platform able to achieve one GFLOPS is listed”, which is manifestly untrue, as the actual listings show milestones in price/performance instead.
Example:  The 2011 entry, at $30,000 overall cost, was added because it was an enormous improvement in price/performance over the 2007 entry, yet that 2007 entry, at $1256, was still the “least expensive”.
If there are no objections, I'd like to rewrite that heading paragraph to more accurately describe the content it introduces.
 Unician ∇  21:45, 28 May 2014 (UTC)
thread_title:  Hardware costs 

message: I would like to add, that the numbers seem inaccurate in general, which might be a result from simply integrating information randomly found on the internet. For instance the last row (October 2007) claims that "Three AMD RX Vega 64 graphics cards provide just over 75 TFLOPS half precision [...] at ~$2,050 for the complete system". The given reference (https://pcpartpicker.com/user/mattebaughman/saved/8DQZ8d) does not give any information regarding the full price of the system. Further the cost of one AMD RX Vega 64 graphic card alone is far above 1000 USD (Amazon (link visited 13.12.2018)). You might get one for ~630 EUR (roughly< 710 USD) at Newegg.com (visited 13.12.2018), however 3x710 = 2100 USD for the Grafic Card alone.
134.28.120.119 (talk) 09:50, 13 December 2018 (UTC)
thread_title:  Hardware costs 2

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thread_title:  External links modified 

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Cheers.—cyberbot IITalk to my owner:Online 06:16, 28 March 2016 (UTC)
thread_title:  External links modified 

message: This article seems to be more about the use of the term than the term itself. I see no history of the term. I am interested in who invented the term. I think IBM invented the term (the idea or whatever) to provide a more useful comparison of their processors compared to Amdahl and other competitors. Sam Tomato (talk) 01:41, 5 May 2016 (UTC)
thread_title:  History 

message: Hello fellow Wikipedians,
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thread_title:  External links modified 

message: In the first table, the same abbreviation (GFLOPS) is given to two terms. Since "geo" is not an official SI prefix, it's highly doubtful – and indeed not possible for avoidance of ambiguity – that "G" would be used to abbreviate "geo". I'm going to remove last two abbreviations from the table (for both "bronto" and "geo"), as both are unofficial prefixes and as such don't have official abbreviations. cherkash (talk) 06:39, 7 January 2017 (UTC)
thread_title:  GFLOPS is (incorrectly?) used for both "giga" and "geo" 

message: The list of cost per GFLOP starts with supercomputers which were the absolute fastest of their time, then switches to clusters of commodity hardware, and then to console and PC hardware. All of these are different types of computers, and it is misleading to compare FLOPs between them. A supercomputer for example is more expensive per FLOP, but offers the biggest absolute computing power at a given time in one system, and meets much higher stability and availability requirements compared to a PC.
Further, even ignoring this over-simplification, the cost per GFLOP numbers from the last years are misleading. One would have a hard time even installing an operating system, and a graphics driver on the hardware that is given as source for the $0.08/GFLOP (http://www.freezepage.com/1420850340WGSMHXRBLE) because of the small SSD and low amount of RAM. 
I suggest to either rework the section to give a more realistic view on the cost of computing power (i.e. compare the same type of systems over time), or to just remove it.
--Aquaschaf (talk) 22:45, 24 May 2017 (UTC)
replies: text: In the 60s, there were only mainframes practically, micro or even mini computers not being invented yet. The table tries to show the cheapest way to achieve GFLOPS speed. It does have some room for improvement, so feel free to add to it. By the way, installing Linux on a 32 GB drive is no problem. Additionally, you could easily exchange the SSD for a larger HDD (and save!) without loss of FLOPS. --Zac67 (talk) 07:45, 25 May 2017 (UTC)
thread_title:  Hardware costs - misleading comparisons 

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thread_title:  External links modified 

message: ...was that even a simple programmable calculator kan perform thousands of consecutive floating point operations without manual intervention. It's only when a person punches at least one button between each operation that 1/10 of a second is neglectable. - Tournesol (talk) 15:59, 16 November 2017 (UTC)
replies: text: Even complex or programmed calculations are usually noticeably slow on a pocket calculator. It's not about manual intervention, the article is about float operations per second. Do you have a source for a simple calculator performing more than "relatively few" FLOPS? Unless it's many KFLOPS that's relatively few for me. For today's standard and in the context of the paragraph, relatively few is everything not measured in GFLOPS. --Zac67 (talk) 17:52, 16 November 2017 (UTC)

text: Great to hear you've sorted it out. ;-) --Zac67 (talk) 18:23, 23 November 2017 (UTC)
thread_title:  What i meant... 

message: One sentence indicates that FLOPS are base two, the next includes IBM base 16 floating point.  This then ignores that IEEE 754-2008 includes decimal (base 10) floating point formats. Gah4 (talk) 19:46, 27 February 2018 (UTC)
thread_title:  base two? 

message: The numbers, particularly past 2000, are way off. The 2007 $57 figure is off by an order of magnitude - calculating the price per GFLOPS performance of an 8800 Ultra from that year yields a $2.1 price tag per GFLOPS and even that's very unlikely to be the best performance per dollar considering it is an enthusiast tier card. Another example in 2011: a GTX 480 is capable of $0.37 per GFLOPS compared to the $1.98 listed. I am unsure of all the figures, but I suspect these are not the only inaccuracies considering that the examples usually use high end consumer graphics cards that are going to be price-inefficient. The whole chart needs a rework past 2000 at least, no idea about other eras. --Krispion (talk) 18:56, 23 September 2018 (UTC)
thread_title:  Cost of Computing section is woefully inaccurate 

message: The word "cycle" is used in the "FLOPs per cycle" section without explanation.  If "cycle" is equivalent to one tick of the processor clock (i.e., the inverse of the clock speed in GHz), this should be stated explicitly.  If not, further explanation should be given.  Also, I think the "s" in FLOPs should be capitalized.  Jess_Riedel (talk) 15:04, 26 September 2018 (UTC)
thread_title:  "Cycle" 

message: I've been looking for an answer to, what seems like, a simple question, and coming up empty handed. What was the first commercial, off the shelf, single chip, stick it in your favorite motherboard, processor that was capable of a sustained 1 gigaflop speed? That wasn't a one-off special chip, that didn't require special/custom hardware, that wasn't a special research project, or required an N-way crossbar connecting X processors with Y memory arrays, in a Beowulf cluster, in order the win the Gordon GoFaster prize? Just whatever advancement/next-step in Pentium/AMD/PowerPC/Whatever came along that allowed the average college-student/gamer to put 1 gigaflop on their desk? I suspect this point was reached right around the year 2000, but I haven't found anything more exact than that.Gcronau (talk) 16:12, 14 January 2019 (UTC)
thread_title:  First Commercial Single-Chip Processor capable of 1 Gigaflop? 

message: I found an article that seems to give a new formula for FLOPS calculus : https://cs.iupui.edu/~fgsong/cs590HPC/how2decide_peak.pdf. I would like to know what you think about it. I'm working on applying it for every CPU that can be evaluated in FLOPS. For example, here the i7-2600 number of FLOPS :
On the Wiki article : https://en.wikipedia.org/wiki/Sandy_Bridge, Whestone benchmark measures 83 GFLOPS for this CPU.
The CPU has 4 cores and 8 threads (HyperThreading Technology available). The CPU runs at 3.40 GHz. It has the SSE and AVX instruction set.
So, for SSE scalar operation, we have : 4 (cores) * 2 (number of thread per core) * 1 (instruction set specific multiplier) * 3.40 = 27.20 GFLOPS
For SSE vector operation (128 bits wide) in double precision, we have : 4 * 2 * 2 (instruction set specific multiplier) * 3.40 = 54.40 GFLOPS
For SSE vector operation (128 bits wide) in simple precision, we have : 4 * 2 * 4 * 3.40 = 108.80 GFLOPS
For AVX vector operation (256 bits wide) in simple precision, we have : 4 * 2 * 8 * 3.40 = 217.60 GFLOPS
Jithel (talk) 13:49, 15 March 2019 (UTC)
replies: text: It is partially correct. However, the FLOPs per core are for the real cores only, not for HT. The two HT siblings share just one FP unit. So your SandyBridge at 3.4GHz with 4 cores with AVX theoretically does 3.4x4x8=108.8 GFLOPs Jfikar (talk) 12:16, 6 November 2023 (UTC)
thread_title:  New FLOPS formula 

message: Besides record values, wouldn't it be interesting to mention estimated FLOPS values of some well known or ″historic″ processors: Zilog Z80, Intel 4004, Intel 8080, Motorola 68000, 80x86 series, PDP-11,...
--Olivier Debre (talk) 18:08, 25 February 2021 (UTC)
replies: text: If you find a reliable website that talks about it, why not, that would be interesting. Bensuperpc (talk) 18:44, 25 February 2021 (UTC)

text: Most of the processors in the list do not have floating point implementations in hardware. Intel offered the x87 coprocessors for this function. 198.85.71.19 (talk) 14:22, 5 June 2023 (UTC)
thread_title:  FLOPS estimation for historical/well known processors 

message: Floating Point Operations Per Second per cycle. That's like saying meters per second per hour. It doesn't make any sense. There has to be a better way of phrasing that 24.192.184.78 (talk) 20:33, 22 June 2022 (UTC)
replies: text: Bothers me as well. Can we use FLOP (for FLoating-point OPeration) here? TOP500 use flop/s. The formula above uses FLOPs, apparently as plural, but I don't think that's really working either. Basically, it boils down to floating IPC. I guess why just shouldn't try to abbreviate. --Zac67 (talk) 05:25, 23 June 2022 (UTC)

text: I think the title was just wrong and the table is actually floating-point operations per cycle (per core). The linked reference shows eg "64 FLOPs/cycle", and further up that page, it says "FLOPS = FLOPs/cycle x cycles/second". I've gone ahead and changed the title to "Floating-point operations per clock cycle for various processors". We should probably make this more concise, but at least it's not wrong now. 158.106.213.34 (talk) 01:33, 15 July 2022 (UTC)
thread_title:  FLOPS per cycle per core 

message: The article states without citation that Frank McMahon at LLNL invented the term. (added here) McMahon wrote a book on benchmarking in the 80s mentioned here, but I can't access it.
While the derivation from "FLoating point OPerationS" is obvious, and I'm sure the term was used informally before it ever appeared in print, I am wondering if this couldn't be figured out in more detail.
I ask because I happened to be reading "Nineteen Dubious Ways to Compute the Exponential of a Matrix" by Moler and van Loan, and it defines the term without citing any previous definitions. That's a 1978 paper that I don't think originated from LLNL. 2603:6081:2340:23A:E47A:E4C7:965F:C2AF (talk) 15:59, 4 December 2022 (UTC)
replies: text: I looked up on Google Books and while there are a lot of talk about McMahon popularizing MFLOPS in the 1980s and a 2020 obituary attributing the term to him probably due to Wikipedia, OED first attests it way back in 1976 and I found the actual first attestation in 1974 by David Kuck which is written like nobody used that term before. That's why I removed McMahon and replaced him with Kuck. 5.178.188.143 (talk) 12:45, 15 January 2024 (UTC)
thread_title:  Origin of term? 

message: With the lowest price per GFLOP being one cent now, I think it may be appropriate to update the chart's metric to $/TFLOPS for more meaningful comparisons going forward that won't require fractions of cents. The fact that it hasn't been done yet is already kinda weird, since the table ends in several entries that each only have one significant figure. Sizniche (talk) 22:00, 27 May 2023 (UTC)
thread_title:  Update "Cost of computing" metric to $/TFLOPS?