Cpu Floating Point Error
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Pentium processors. Because of the bug, the processor could return incorrect decimal results when dividing a number. Discovered in 1994 by Professor Thomas R. Nicely at Lynchburg College,[1] cpu floating point operations per second Intel attributed the error to missing entries in the lookup table used by cpu floating point benchmark the floating-point division circuitry.[2] The severity of the FDIV bug is debated. Intel, producer of the affected chip, claims that the
Floating Point Rounding Error
common user would experience it once every 27,000 years while IBM, manufacturer of a chip competing with Intel's Pentium, claims that the common user would experience it once every 24 days. Though rarely
Floating Point Relative Error
encountered by most users (Byte magazine estimated that 1 in 9 billion floating point divides with random parameters would produce inaccurate results),[3] both the flaw and Intel's initial handling of the matter were heavily criticized by the tech community. The man who found the bug points out that since it went unnoticed for a year in a popular product, that likely indicates that the bug was less invalid floating point operation error harmful than IBM suggested. Intel ultimately recalled the defective processors. Contents 1 Chronology 2 Affected models 3 Example symptoms 4 See also 5 References 6 External links Chronology[edit] Thomas Nicely, a professor of mathematics at Lynchburg College, had written code to enumerate primes, twin primes, prime triplets, and prime quadruplets. Nicely noticed some inconsistencies in the calculations on June 13, 1994, shortly after adding a Pentium system to his group of computers, but was unable to eliminate other factors (such as programming errors, motherboard chipsets, etc.) until October 19, 1994. On October 24, 1994, he reported the issue to Intel. According to Nicely, his contact person at Intel later admitted that Intel had been aware of the problem since May 1994, when the flaw was discovered by Tom Kraljevic, a Purdue co-op student working for Intel in Hillsboro, Oregon, during testing of the FPU for its new P6 core, first used in the Pentium Pro. On October 30, 1994, Nicely sent an email describing the error he had discovered in the Pentium floating point unit to various contacts, requesting reports of testing for the flaw on 486-DX4s, Pentiums and Pentium clones.[1] This flaw in the Pentium FPU was quickly ver
the world Pentium FDIV: The processor bug that shook the world By Desire Athow Processors 20 years already Shares This week we celebrate the 20th
Floating Point Overflow Error
anniversary of the FDIV bug, an error in the then-new Intel Pentium floating point exception error processor. It was discovered by Thomas Nicely, a professor of mathematics, on 19 October 1994 and reported to floating point error matlab Intel five days later. Then on 30 October 1994, he wrote a fateful email to "a number of individuals and organizations" that set the wheels in motion.The processor floating-point divide https://en.wikipedia.org/wiki/Pentium_FDIV_bug problem was caused by a subtle but specific circuit-design error; the flaw was easily corrected with changes to masks in the next regular production revision of the chip, in 1994.Although its actual impact would have been negligible, it then snowballed into something much bigger, thanks to national press coverage and can legitimately be called the first computer hardware problem http://www.techradar.com/news/computing-components/processors/pentium-fdiv-the-processor-bug-that-shook-the-world-1270773 to have made the headline worldwide, well before the Millennium Bug.Subsequent processor related bugs like the TSX one that hit Haswell processors in August still make the headlines but only in tech and not in such a dramatic fashion.Why was there a bug in the first place? Well, because microprocessors are such complicated pieces of technology that, even back then, involves millions of transistors. The whole industry was still learning about tools, processes (steppings) and mechanisms (like microcode, firmware updates) that would help reduce defects and errors but even today, bugs are very much part and parcel of any processor. We asked Intel for some background on how the company lived through what could be called its first real PR crisis and Tom Waldrop, an Intel veteran who witnessed first-hand the drama unravel, was kind enough to contribute [note that his account is entirely based on Andy Grove's "Only the paranoid survive" and Albert Yu's "Creating the Digital Future: The Secrets of Consistent Innovation at Intel".]"Intel learnt a lot from that issue; previously, the firm had be
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about http://stackoverflow.com/questions/2100490/floating-point-inaccuracy-examples hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up Floating point inaccuracy examples up vote 29 down vote favorite 46 How do you explain floating point inaccuracy to fresh programmers and laymen who still think computers are infinitely floating point wise and accurate? Do you have a favourite example or anecdote which seems to get the idea across much better than an precise, but dry, explanation? How is this taught in Computer Science classes? floating-point floating-accuracy share edited Apr 24 '10 at 22:34 community wiki 4 revs, 3 users 57%David Rutten locked by Bill the Lizard May 6 '13 at 12:41 This question exists because it has historical significance, but it is not considered a good, on-topic question cpu floating point for this site, so please do not use it as evidence that you can ask similar questions here. This question and its answers are frozen and cannot be changed. More info: help center. Take a look into this article: What Every Computer Scientist Should Know About Floating-Point Arithmetic –Rubens Farias Jan 20 '10 at 10:17 1 You can comprove this with this simple javascript:alert(0.1*0.1*10); –user216441 Apr 24 '10 at 23:07 comments disabled on deleted / locked posts / reviews| 7 Answers 7 active oldest votes up vote 26 down vote accepted There are basically two major pitfalls people stumble in with floating-point numbers. The problem of scale. Each FP number has an exponent which determines the overall “scale” of the number so you can represent either really small values or really larges ones, though the number of digits you can devote for that is limited. Adding two numbers of different scale will sometimes result in the smaller one being “eaten” since there is no way to fit it into the larger scale. PS> $a = 1; $b = 0.0000000000000000000000001 PS> Write-Host a=$a b=$b a=1 b=1E-25 PS> $a + $b 1 As an analogy for this case you could picture a large swimming pool and a teaspoon of water. Both are of very different sizes, but individually you can easily grasp how much they roughly are. Pouring the teaspoon