Units of information
In computing and telecommunications, a unit of information is the capacity of some standard data storage system or communication channel, used to measure the capacities of other systems and channels. In information theory, units of information are also used to measure the information contents or entropy of random variables.
The most common units are the bit, the capacity of a system which can exist in only two states, and the byte (or octet), which is equivalent to eight bits. Multiples of these units can be formed from these with the SI prefixes (power-of-ten prefixes) or the newer IEC binary prefixes (binary power prefixes). Information capacity is a dimensionless quantity, because it refers to a count of binary symbols.
Primary units
In 1928, Ralph Hartley observed a fundamental storage principle,[1] which was further formalized by Claude Shannon in 1945: the information that can be stored in a system is proportional to the logarithm logb N of the number N of possible states of that system. Changing the basis of the logarithm from b to a different number c has the effect of multiplying the value of the logarithm by a fixed constant, namely logc N = (logc b) logb N. Therefore, the choice of the basis b determines the unit used to measure information. In particular, if b is a positive integer, then the unit is the amount of information that can be stored in a system with b possible states.
When b is 2, the unit is the "bit" (a contraction of binary digit). A system with 8 possible states, for example, can store up to log28 = 3 bits of information. Other units that have been named include:
- Base b = 3: the unit is called "trit", and is equal to log2 3 (≈ 1.585) bits.[2]
- Base b = 10: the unit is called decimal digit, Hartley, ban, decit, or dit, and is equal to log2 10 (≈ 3.322) bits.[1][3][4][5]
- Base b = e, the base of natural logarithms: the unit is called a nat, nit, or nepit (from Neperian), and is worth log2 e (≈ 1.443) bits.[1]
The trit, ban, and nat are rarely used to measure storage capacity; but the nat, in particular, is often used in information theory, because natural logarithms are sometimes easier to handle than logarithms in other bases.
Units derived from bit
Several conventional names are used for collections or groups of bits.
Byte
Historically, a byte was the number of bits used to encode a character of text in the computer, which depended on computer hardware architecture; but today it almost always means eight bits — that is, an octet. A byte can represent 28 = 256 distinct values, such as the integers 0 to 255, or -128 to 127. The IEEE 1541-2002 standard specifies "B" (upper case) as the symbol for byte. Bytes, or multiples thereof, are almost always used to specify the sizes of computer files and the capacity of storage units. Most modern computers and peripheral devices are designed to manipulate data in whole bytes or groups of bytes, rather than individual bits.
Nibble
A group of four bits, or half a byte, is sometimes called a nibble or nybble. This unit is most often used in the context of hexadecimal number representations, since a nibble has the same amount of information as one hexadecimal digit.[6]
Word, block, and page
Computers usually manipulate bits in groups of a fixed size, conventionally called words. The number of bits in a word is usually defined by the size of the registers in the computer's CPU, or by the number of data bits that are fetched from its main memory in a single operation. In the IA-32 architecture more commonly known as x86-32, a word is 16 bits, but other past and current architectures use words with 8, 24, 32, 36, 51, 64, 80 bits or others.
Some machine instructions and computer number formats use two words (a "double word" or "dword"), or four words (a "quad word" or "quad").
Computer memory caches usually operate on blocks of memory that consist of several consecutive words. These units are customarily called cache blocks, or, in CPU caches, cache lines.
Virtual memory systems partition the computer's main storage into even larger units, traditionally called pages.
Systematic multiples
Terms for large quantities of bits can be formed using the standard range of SI prefixes for powers of 10, e.g., kilo = 103 = 1000 (kilobit or kbit), mega- = 106 = 1000000 (megabit or Mbit) and giga = 109 = 1000000000 (gigabit or Gbit). These prefixes are more often used for multiples of bytes, as in kilobyte (kB = 8000 bits), megabyte (1 MB = 8000000bits), and gigabyte (1 GB = 8000000000bits).
However, for technical reasons, the capacities of computer memories and some storage units are often multiples of some large power of two, such as 228 = 268435456 bytes. To avoid such unwieldy numbers, people have often misused the SI prefixes to mean the nearest power of two, e.g., using the prefix kilo for 210 = 1024, mega for 220 = 1048576, and giga for 230 = 1073741824, and so on. For example, a random access memory chip with a capacity of 228 bytes would be referred to as a 256-megabyte chip. The table below illustrates these differences.
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Orders of magnitude of data |
Symbol | Prefix | SI Meaning | Binary meaning | Size difference |
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K | kilo | 103 = 10001 | 210 = 10241 | 2.40% |
M | mega | 106 = 10002 | 220 = 10242 | 4.86% |
G | giga | 109 = 10003 | 230 = 10243 | 7.37% |
T | tera | 1012 = 10004 | 240 = 10244 | 9.95% |
P | peta | 1015 = 10005 | 250 = 10245 | 12.59% |
E | exa | 1018 = 10006 | 260 = 10246 | 15.29% |
Z | zetta | 1021 = 10007 | 270 = 10247 | 18.06% |
Y | yotta | 1024 = 10008 | 280 = 10248 | 20.89% |
In the past, uppercase K has been used instead of lowercase k to indicate 1024 instead of 1000. However, this usage was never consistently applied.
On the other hand, for external storage systems (such as optical disks), the SI prefixes were commonly used with their decimal values (powers of 10). There have been many attempts to resolve the confusion by providing alternative notations for power-of-two multiples. In 1998 the International Electrotechnical Commission (IEC) issued a standard for this purpose, namely a series of binary prefixes that use 1024 instead of 1000 as the main radix:[7]
Multiple-byte units | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Orders of magnitude of data |
Symbol | Prefix | |||
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Ki | kibi, binary kilo | 1 kibibyte (KiB) | 210 bytes | 1024 B |
Mi | mebi, binary mega | 1 mebibyte (MiB) | 220 bytes | 1024 KiB |
Gi | gibi, binary giga | 1 gibibyte (GiB) | 230 bytes | 1024 MiB |
Ti | tebi, binary tera | 1 tebibyte (TiB) | 240 bytes | 1024 GiB |
Pi | pebi, binary peta | 1 pebibyte (PiB) | 250 bytes | 1024 TiB |
Ei | exbi, binary exa | 1 exbibyte (EiB) | 260 bytes | 1024 PiB |
The JEDEC memory standards however define uppercase K, M, and G for the binary powers 210, 220, 230, and 240 to reflect common usage.[8]
Size examples
- 90 bytes: enough to store a typical line of text from a book.
- 512 bytes = ½ KiB: the typical sector of a hard disk.
- 1024 bytes = 1 KiB: the classical block size in UNIX filesystems.
- 2048 bytes = 2 KiB: a CD-ROM sector.
- 4096 bytes = 4 KiB: a memory page in x86 (since Intel 80386).
- 4 kB: about one page of text from a novel.
- 120 kB: the text of a typical pocket book.
This section needs expansion. You can help by adding to it. (June 2008) |
Obsolete and unusual units
Several other units of information storage have been named.[6]:
- 1 bit: sniff.[citation needed]
- 2 bits: crumb, quad, quarter, tayste, tydbit, semi-nibble.
- 5 bits: nickel, nyckle.[citation needed]
- 6 bits: byte (in early IBM machines using BCD alphamerics).
- 10 bits: deckle, dyme.[citation needed]
- 16 bits: doublet, plate, playte, chomp, chawmp (on a 32-bit machine).[citation needed]
- 18 bits: chomp, chawmp (on a 36-bit machine).[citation needed]
- 32 bits: quadlet, dinner, dynner, gawble (on a 32-bit machine).[citation needed]
- 48 bits: gobble, gawble (under circumstances that remain obscure).[citation needed]
- 64 bits: octlet.[citation needed]
- 256 bytes: paragraph
- 6 trits: tryte [9]
Most of these names are jargon, obsolete, or used only in very restricted contexts.
References
- ^ a b c Norman Abramson (1963), Information theory and coding. McGraw-Hill.
- ^ Donald E. Knuth, The Art of Computer programming, vol.2: Seminumerical algorithms.
- ^ Shanmugam (2006), Digital and Analog Computer Systems.
- ^ Gregg Jaeger (2007), [1]Quantum information: an overview'
- ^ I. Ravi Kumar (2001), Comprehensive Statistical Theory of Communication.
- ^ a b Nybble at dictionary reference.com; sourced from Jargon File 4.2.0, accessed 2007-08-12
- ^ ISO/IEC standard is ISO/IEC 80000-13:2008. Not publicly available. This standard cancels and replaces subclauses 3.8 and 3.9 of IEC 60027-2:2005. The only significant change is the addition of explicit definitions for some quantities. ISO Online Catalogue
- ^
JEDEC Solid State Technology Association (December 2002). "Terms, Definitions, and Letter Symbols for Microcomputers, Microprocessors, and Memory Integrated Circuits" (PDF). JESD 100B.01. Retrieved 5 April 2009Template:Inconsistent citations
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: CS1 maint: postscript (link) - ^ Brousentsov, N. P.; Maslov, S. P.; Ramil Alvarez, J.; Zhogolev, E.A. "Development of ternary computers at Moscow State University". Retrieved 20 January 2010.