• Source: Computer performance by orders of magnitude

This list compares various amounts of computing power in instructions per second organized by order of magnitude in FLOPS.




Milliscale computing (10−3)


2×10−3: average human multiplication of two 10-digit numbers using pen and paper without aids




Deciscale computing (10−1)


1×10−1: multiplication of two 10-digit numbers by a 1940s electromechanical desk calculator
3×10−1: multiplication on Zuse Z3 and Z4, first programmable digital computers, 1941 and 1945 respectively
5×10−1: computing power of the average human mental calculation for multiplication using pen and paper




Scale computing (100)


1.2 OP/S: addition on Z3, 1941, and multiplication on Bell Model V, 1946
2.4 OP/S: addition on Z4, 1945




Decascale computing (101)


1.8×101: ENIAC, first programmable electronic digital computer, 1945
5×101: upper end of serialized human perception computation (light bulbs do not flicker to the human observer)
7×101: Whirlwind I 1951 vacuum tube computer and IBM 1620 1959 transistorized scientific minicomputer




Hectoscale computing (102)


1.3×102: PDP-4 commercial minicomputer, 1962
2×102: IBM 602 electromechanical calculator (then called computer), 1946
6×102: Manchester Mark 1 electronic general-purpose stored-program digital computer, 1949




Kiloscale computing (103)


2×103: UNIVAC I, first American commercially available electronic general-purpose stored program digital computer, 1951
3×103: PDP-1 commercial minicomputer, 1959
15×103: IBM Naval Ordnance Research Calculator, 1954
24×103: AN/FSQ-7 Combat Direction Central, 1957
30×103: IBM 1130 commercial minicomputer, 1965
40×103: multiplication on Hewlett-Packard 9100A early desktop electronic calculator, 1968
53×103: Lincoln TX-2 transistor-based computer, 1958
92×103: Intel 4004, first commercially available full function CPU on a chip, released in 1971
500×103: Colossus computer vacuum tube cryptanalytic supercomputer, 1943




Megascale computing (106)


1×106: computing power of the Motorola 68000 commercial computer introduced in 1979. This is also the minimum computing power of a Type 0 Kardashev civilization.
1.2×106: IBM 7030 "Stretch" transistorized supercomputer, 1961
5×106: CDC 6600, first commercially successful supercomputer, 1964
11×106: Intel i386 microprocessor at 33 MHz, 1985
14×106: CDC 7600 supercomputer, 1967
40×106: i486 microprocessor at 50 MHz, 1989
86×106: Cray 1 supercomputer, 1978
100×106: Pentium (i586) microprocessor, 1993
400×106: Cray X-MP, 1982




Gigascale computing (109)


1×109: ILLIAC IV 1972 supercomputer does first computational fluid dynamics problems
1.4×109: Intel Pentium III microprocessor, 1999
1.6×109: PowerVR MBX Lite 3D GPU on iPhone 1, 2007
8×109: PowerVR SGX535 GPU on iPad 1, 2010
136×109: PowerVR GXA6450 GPU on iPhone 6 and iPhone SE, 2014
148×109: Intel Core i7-980X Extreme Edition commercial computing 2010




Terascale computing (1012)


1.34×1012: Intel ASCI Red 1997 supercomputer
1.344×1012 GeForce GTX 480 in 2010 from Nvidia at its peak performance
2.15×1012: iPhone 15 Pro September 2023 A17 Pro processor
4.64×1012: Radeon HD 5970 in 2009 from AMD (under ATI branding) at its peak performance
5.152×1012: S2050/S2070 1U GPU Computing System from Nvidia
11.3×1012: GeForce GTX 1080 Ti in 2017
13.7×1012: Radeon RX Vega 64 in 2017
15.0×1012: Nvidia Titan V in 2017
80×1012: IBM Watson
170×1012: Nvidia DGX-1 The initial Pascal based DGX-1 delivered 170 teraflops of half precision processing.
478.2×1012 IBM BlueGene/L 2007 Supercomputer
960×1012 Nvidia DGX-1 The Volta-based upgrade increased calculation power of Nvidia DGX-1 to 960 teraflops.




Petascale computing (1015)



1.026×1015: IBM Roadrunner 2009 Supercomputer
1.32×1015: Nvidia GeForce 40 series' RTX 4090 consumer graphics card achieves 1.32 petaflops in AI applications, October 2022
2×1015: Nvidia DGX-2 a 2 Petaflop Machine Learning system (the newer DGX A100 has 5 Petaflop performance)
10×1015: minimum computing power of a Type I Kardashev civilization
11.5×1015: Google TPU pod containing 64 second-generation TPUs, May 2017
17.17×1015: IBM Sequoia's LINPACK performance, June 2013
20×1015: roughly the hardware-equivalent of the human brain according to Ray Kurzweil. Published in his 1999 book: The Age of Spiritual Machines: When Computers Exceed Human Intelligence
33.86×1015: Tianhe-2's LINPACK performance, June 2013
36.8×1015: 2001 estimate of computational power required to simulate a human brain in real time.
93.01×1015: Sunway TaihuLight's LINPACK performance, June 2016
143.5×1015: Summit's LINPACK performance, November 2018




Exascale computing (1018)



1×1018: Fugaku 2020 Japanese supercomputer in single precision mode
1.1x1018: Frontier 2022 U.S. supercomputer
1.88×1018: U.S. Summit achieves a peak throughput of this many operations per second, whilst analysing genomic data using a mixture of numerical precisions.
2.43×1018 Folding@home distributed computing system during COVID-19 pandemic response




Zettascale computing (1021)



1×1021: Accurate global weather estimation on the scale of approximately 2 weeks. Assuming Moore's law remains applicable, such systems may be feasible around 2035.
A zettascale computer system could generate more single floating point data in one second than was stored by any digital means on Earth in the first quarter of 2011.




Beyond zettascale computing (>1021)


1.12×1036: Estimated computational power of a Matrioshka brain, assuming 1.87×1026 watt power produced by solar panels and 6 GFLOPS/watt efficiency.
4×1048: Estimated computational power of a Matrioshka brain whose power source is the Sun, the outermost layer operates at 10 kelvins, and the constituent parts operate at or near the Landauer limit and draws power at the efficiency of a Carnot engine
5×1058: Estimated power of a galaxy equivalent in luminosity to the Milky Way converted into Matrioshka brains.




See also


Futures studies – study of possible, probable, and preferable futures, including making projections of future technological advances
History of computing hardware (1960s–present)
List of emerging technologies – new fields of technology, typically on the cutting edge. Examples include genetics, robotics, and nanotechnology (GNR)
Artificial intelligence – computer mental abilities, especially those that previously belonged only to humans, such as speech recognition, natural language generation, etc.
History of artificial intelligence (AI)
Strong AI – hypothetical AI as smart as a human
Quantum computing
Timeline of quantum computing and communication
Moore's law – observation (not actually a law) that, over the history of computing hardware, the number of transistors on integrated circuits doubles approximately every two years. The law is named after Intel co-founder Gordon Moore, who described the trend in his 1965 paper.
Supercomputer
History of supercomputing
Superintelligence
Timeline of computing
Technological singularity – hypothetical point in the future when computer capacity rivals that of a human brain, enabling the development of strong AI — artificial intelligence at least as smart as a human
The Singularity Is Near – book by Raymond Kurzweil dealing with the progression and projections of development of computer capabilities, including beyond human levels of performance
TOP500 – list of the 500 most powerful (non-distributed) computer systems in the world




References






External links


Historical and projected growth in supercomputer capacity

Kata Kunci Pencarian:

• Computer performance by orders of magnitude
• Computer performance
• Orders of magnitude (mass)
• Hazard (computer architecture)
• Exascale computing
• Outline of computers
• Floating point operations per second
• Adder (electronics)
• Outline of computer engineering
• Memory-mapped I/O and port-mapped I/O