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Measure of estimator performance

For other uses, see Bomb.

Computer performance
Name Unit Value
kiloFLOPS kFLOPS 10iii
megaFLOPS MFLOPS ten6
gigaFLOPS GFLOPS xix
teraFLOPS TFLOPS 1012
petaFLOPS PFLOPS 1015
exaFLOPS EFLOPS ten18
zettaFLOPS ZFLOPS ten21
yottaFLOPS YFLOPS 1024

In computing, floating point operations per second (FLOPS, flops or flop/south) is a measure of reckoner performance, useful in fields of scientific computations that crave floating-signal calculations. For such cases, information technology is a more accurate measure than measuring instructions per second.

Floating-point arithmetic [edit]

Floating-point arithmetics is needed for very large or very small real numbers, or computations that require a large dynamic range. Floating-betoken representation is similar to scientific note, except everything is carried out in base two, rather than base of operations ten. The encoding scheme stores the sign, the exponent (in base two for Cray and VAX, base ii or 10 for IEEE floating point formats, and base xvi for IBM Floating Point Architecture) and the Significand (number after the radix betoken). While several similar formats are in utilize, the almost common is ANSI/IEEE Std. 754-1985. This standard defines the format for 32-fleck numbers chosen single precision, as well equally 64-bit numbers chosen double precision and longer numbers called extended precision (used for intermediate results). Floating-bespeak representations can support a much wider range of values than fixed-bespeak, with the ability to represent very small numbers and very large numbers.[ane]

Dynamic range and precision [edit]

The exponentiation inherent in floating-point ciphering assures a much larger dynamic range – the largest and smallest numbers that tin be represented – which is especially important when processing information sets where some of the data may have extremely big range of numerical values or where the range may be unpredictable. As such, floating-indicate processors are ideally suited for computationally intensive applications.[2]

Computational performance [edit]

FLOPS and MIPS are units of mensurate for the numerical calculating performance of a calculator. Floating-point operations are typically used in fields such as scientific computational inquiry. The unit MIPS measures integer functioning of a reckoner. Examples of integer operation include data movement (A to B) or value testing (If A = B, then C). MIPS as a performance criterion is adequate when a computer is used in database queries, word processing, spreadsheets, or to run multiple virtual operating systems.[iii] [four] Frank H. McMahon, of the Lawrence Livermore National Laboratory, invented the terms FLOPS and MFLOPS (megaFLOPS) and so that he could compare the 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 equally this statistic commonly had lilliputian bearing on the arithmetic capability of the automobile.

FLOPS on an HPC-system tin can be calculated using this equation:

FLOPS = racks × nodes rack × sockets node × cores socket × cycles second × FLOPs cycle . {\displaystyle {\text{FLOPS}}={\text{racks}}\times {\frac {\text{nodes}}{\text{rack}}}\times {\frac {\text{sockets}}{\text{node}}}\times {\frac {\text{cores}}{\text{socket}}}\times {\frac {\text{cycles}}{\text{2nd}}}\times {\frac {\text{FLOPs}}{\text{bicycle}}}.}

This tin be simplified to the almost mutual case: a reckoner that has exactly 1 CPU:

FLOPS = cores × cycles 2nd × FLOPs cycle . {\displaystyle {\text{FLOPS}}={\text{cores}}\times {\frac {\text{cycles}}{\text{second}}}\times {\frac {\text{FLOPs}}{\text{cycle}}}.}

FLOPS can be recorded in different measures of precision, for instance, the TOP500 supercomputer listing ranks computers past 64 bit (double-precision floating-betoken format) operations per second, abbreviated to FP64.[half-dozen] Like measures are available for 32-chip (FP32) and 16-scrap (FP16) operations.

FLOPS per cycle per core for various processors [edit]

FLOPS per core[7]
Microarchitecture ISA FP64 FP32 FP16
Intel CPU
Intel 80486 x87 (32-bit) ? 0.128[8] ?
  • Intel P5 Pentium
  • Intel P6 Pentium Pro
 x87 (32-bit) ? 0.v[8] ?
  • Intel P5 Pentium MMX
  • Intel P6 Pentium Two
 MMX (64-bit) ? 1[9] ?
Intel P6 Pentium Iii SSE (64-scrap) ? two[9] ?
Intel Netburst Pentium 4 (Willamette, Northwood) SSE2 (64-flake) 2 4 ?
Intel P6 Pentium M SSE2 (64-bit) 1 2 ?
  • Intel Netburst Pentium 4 (Prescott, Cedar Mill)
  • Intel Netburst Pentium D (Smithfield, Presler)
  • Intel P6 Core (Yonah)
 SSE3 (64-bit) 2 iv ?
  • Intel Core (Merom, Penryn)
  • Intel Nehalem[x] (Nehalem, Westmere)
  • SSSE3 (128-flake)
  • SSE4 (128-bit)
 4 viii ?
Intel Atom (Bonnell, Saltwell, Silvermont and Goldmont) SSE3 (128-bit) 2 4 ?
Intel Sandy Span (Sandy Bridge, Ivy Bridge) AVX (256-bit) 8 16 0
  • Intel Haswell[10] (Haswell, Devil's Canyon, Broadwell)
  • Intel Skylake (Skylake, Kaby Lake, Coffee Lake, Comet Lake, Whiskey Lake, Amber Lake)
 AVX2 & FMA (256-bit) xvi 32 0
Intel Xeon Phi (Knights Corner) IMCI (512-bit) 16 32 0
  • Intel Skylake-X (Skylake-Ten, Pour Lake)
  • Intel Xeon Phi (Knights Landing, Knights Manufacturing plant)
  • Intel Ice Lake, Tiger Lake and Rocket Lake
 AVX-512 & FMA (512-bit) 32 64 0
AMD CPU
AMD Bobcat AMD64 (64-flake) 2 4 0
  • AMD Jaguar
  • AMD Puma
 AVX (128-chip) 4 8 0
AMD K10 SSE4/4a (128-scrap) iv 8 0
AMD Bulldozer[10] (Piledriver, Steamroller, Excavator)
  • AVX (128-chip) Bulldozer-Steamroller
  • AVX2 (128-bit) Excavator
  • FMA3 (Bulldozer)[11]
  • FMA3/four (Piledriver-Excavator)
 4 eight 0
  • AMD Zen (Ryzen k series, Threadripper 1000 series, Epyc Naples)
  • AMD Zen+[ten] [12] [13] [14] (Ryzen 2000 series, Threadripper 2000 series)
 AVX2 & FMA (128-bit, 256-bit decoding)[xv] viii sixteen 0
  • AMD Zen ii[16] (Ryzen 3000 series, Threadripper 3000 series, Epyc Rome))
  • AMD Zen 3 (Ryzen 5000 series)
 AVX2 & FMA (256-chip) 16 32 0
ARM CPU
ARM Cortex-A7, A9, A15 ARMv7 1 viii 0
ARM Cortex-A32, A35, A53, A55, A72, A73, A75 ARMv8 ii 8 0
ARM Cortex-A57[x] ARMv8 four 8 0
ARM Cortex-A76, A77, A78 ARMv8 8 16 0
ARM Cortex-X1 ARMv8 xvi 32 ?
Qualcomm Krait ARMv8 one 8 0
Qualcomm Kryo (1xx - 3xx) ARMv8 2 8 0
Qualcomm Kryo (4xx - 5xx) ARMv8 8 16 0
Samsung Exynos M1 and M2 ARMv8 2 8 0
Samsung Exynos M3 and M4 ARMv8 3 12 0
IBM PowerPC A2 (Blueish Gene/Q) ? 8 viii (as FP64) 0
Hitachi SH-iv[17] [18] SH-four 1 7 0
Nvidia GPU
Nvidia Curie (GeForce 6 series and GeForce vii series) PTX ? 8 ?
Nvidia Tesla 2.0 (GeForce GTX 260-295) PTX ? two ?
Nvidia Fermi (only GeForce GTX 465–480, 560 Ti, 570-590) PTX i/4 (locked by driver, 1 in hardware) ii 0
Nvidia Fermi (only Quadro 600-2000) PTX 1/eight 2 0
Nvidia Fermi (only Quadro 4000–7000, Tesla) PTX one ii 0
Nvidia Kepler (GeForce (except Titan and Titan Black), Quadro (except K6000), Tesla K10) PTX 1/12 (for GK110: locked by commuter, 2/3 in hardware) 2 0
Nvidia Kepler (GeForce GTX Titan and Titan Black, Quadro K6000, Tesla (except K10)) PTX two/three 2 0
  • Nvidia Maxwell
  • Nvidia Pascal (all except Quadro GP100 and Tesla P100)
 PTX 1/16 2 i/32
Nvidia Pascal (only Quadro GP100 and Tesla P100) PTX 1 2 iv
Nvidia Volta[xix] PTX 1 two (FP32) + two (INT32) xvi
Nvidia Turing (only GeForce 16XX) PTX 1/16 2 (FP32) + two (INT32) four
Nvidia Turing (all except GeForce 16XX) PTX 1/16 2 (FP32) + 2 (INT32) xvi
Nvidia Ampere[20] [21] (simply Tesla A100/A30) PTX 2 2 (FP32) + 2 (INT32) 32
Nvidia Ampere (all GeForce and Quadro, Tesla A40/A10) PTX ane/32 2 (FP32) + 0 (INT32) or one (FP32) + 1 (INT32) 8
AMD GPU
AMD TeraScale i (Radeon HD 4000 series) TeraScale one 0.4 two ?
AMD TeraScale 2 (Radeon Hard disk 5000 series) TeraScale 2 1 two ?
AMD TeraScale 3 (Radeon HD 6000 series) TeraScale 3 i 4 ?
AMD GCN (only Radeon Pro Due west 8100-9100) GCN 1 two ?
AMD GCN (all except Radeon Pro W 8100-9100, Vega 10-xx) GCN 1/8 ii iv
AMD GCN Vega 10 GCN 1/8 two iv
AMD GCN Vega 20 (only Radeon 7) GCN 1/2 (locked by commuter, 1 in hardware) 2 4
AMD GCN Vega twenty (only Radeon Instinct MI50 / MI60 and Radeon Pro Vii) GCN one 2 four
  • AMD RDNA[22] [23]
  • AMD RDNA two
 RDNA ane/8 2 4
AMD CDNA CDNA 1 iv (Tensor)[24] 16
AMD CDNA 2 CDNA 2 4 (Tensor) four (Tensor) 16
Qualcomm GPU
Qualcomm Adreno 5x0 Adreno 5xx ane ii four
Qualcomm Adreno 6x0 Adreno 6xx 1 two four
Graphcore
Graphcore Colossus GC2[25] [26] [27] (values estimated) ? 0 18 72
Graphcore Colossus GC200 Mk2[28] (values estimated) ? 0 36 144
Supercomputer
ENIAC @ 100 Khz with 385 Flops[29]
48-bit processor @ 208 kHz in CDC 1604 in 1960
lx-fleck processor @ 10 Mhz in CDC6600 in 1964 0.iii (FP60)
lx-bit processor @ 10 Mhz in CDC7600 in 1967 ane.0 (FP60) [xxx]
Cray-1 @ 80 Mhz in 1976 ii
CDC Cyber 205 @ l Mhz in 1981 FORTRAN compiler

(ANSI 77 with vector extensions)

8 16
Microarchitecture ISA FP64 FP32 FP16

Functioning records [edit]

Single calculator records [edit]

In June 1997, Intel's ASCI Red was the world's first reckoner to achieve one teraFLOPS and beyond. Sandia director Neb Campsite said that ASCI Ruby had the all-time reliability of whatsoever supercomputer ever built, and "was supercomputing's loftier-h2o marker in longevity, price, and performance".[31]

NEC's SX-9 supercomputer was the world's commencement vector processor to exceed 100 gigaFLOPS per unmarried cadre.

In June 2006, a new computer was announced by Japanese research establish RIKEN, the MDGRAPE-three. The computer'southward performance tops out at one petaFLOPS, almost ii times faster than the Bluish Gene/50, but MDGRAPE-3 is not a full general purpose computer, which is why it does non appear in the Top500.org list. It has special-purpose pipelines for simulating molecular dynamics.

By 2007, Intel Corporation unveiled the experimental multi-core POLARIS chip, which achieves 1 teraFLOPS at three.xiii GHz. The 80-cadre chip can raise this consequence to 2 teraFLOPS at 6.26 GHz, although the thermal dissipation at this frequency exceeds 190 watts.[32]

In June 2007, Top500.org reported the fastest computer in the world to exist the IBM Bluish Gene/50 supercomputer, measuring a peak of 596 teraFLOPS.[33] The Cray XT4 hit second place with 101.seven teraFLOPS.

On June 26, 2007, IBM announced the 2d generation of its meridian supercomputer, dubbed Blue Gene/P and designed to continuously operate at speeds exceeding 1 petaFLOPS, faster than the Blue Gene/L. When configured to do so, it can reach speeds in excess of three petaFLOPS.[34]

On October 25, 2007, NEC Corporation of Nihon issued a printing release announcing its SX serial model SX-9,[35] challenge it to be the globe's fastest vector supercomputer. The SX-9 features the first CPU capable of a peak vector performance of 102.four gigaFLOPS per unmarried core.

On February 4, 2008, the NSF and the University of Texas at Austin opened full scale enquiry runs on an AMD, Lord's day supercomputer named Ranger,[36] the most powerful supercomputing arrangement in the world for open science inquiry, which operates at sustained speed of 0.5 petaFLOPS.

On May 25, 2008, an American supercomputer built by IBM, named 'Roadrunner', reached the computing milestone of i petaFLOPS. It headed the June 2008 and Nov 2008 TOP500 listing of the about powerful supercomputers (excluding grid computers).[37] [38] The computer is located at Los Alamos National Laboratory in New United mexican states. The computer's proper name refers to the New United mexican states country bird, the greater roadrunner (Geococcyx californianus).[39]

In June 2008, AMD released ATI Radeon Hard disk 4800 series, which are reported to exist the kickoff GPUs to accomplish one teraFLOPS. On Baronial 12, 2008, AMD released the ATI Radeon HD 4870X2 graphics carte du jour with two Radeon R770 GPUs totaling 2.iv teraFLOPS.

In November 2008, an upgrade to the Cray Jaguar supercomputer at the Department of Energy'southward (DOE'southward) Oak Ridge National Laboratory (ORNL) raised the system's computing ability to a meridian 1.64 petaFLOPS, making Jaguar the world'due south first petaFLOPS system defended to open up research. In early 2009 the supercomputer was named subsequently a mythical creature, Kraken. Kraken was declared the earth's fastest university-managed supercomputer and sixth fastest overall in the 2009 TOP500 listing. In 2010 Kraken was upgraded and can operate faster and is more powerful.

In 2009, the Cray Jaguar performed at 1.75 petaFLOPS, chirapsia the IBM Roadrunner for the number one spot on the TOP500 list.[twoscore]

In Oct 2010, Red china unveiled the Tianhe-1, a supercomputer that operates at a peak computing rate of ii.5 petaFLOPS.[41] [42]

As of 2010[update] the fastest PC processor reached 109 gigaFLOPS (Intel Core i7 980 XE)[43] in double precision calculations. GPUs are considerably more powerful. For example, Nvidia Tesla C2050 GPU computing processors perform around 515 gigaFLOPS[44] in double precision calculations, and the AMD FireStream 9270 peaks at 240 gigaFLOPS.[45]

In November 2011, it was announced that Nippon had achieved 10.51 petaFLOPS with its K computer.[46] It has 88,128 SPARC64 VIIIfx processors in 864 racks, with theoretical performance of eleven.28 petaFLOPS. It is named afterward the Japanese word "kei", which stands for 10 quadrillion,[47] corresponding to the target speed of 10 petaFLOPS.

On November 15, 2011, Intel demonstrated a unmarried x86-based processor, code-named "Knights Corner", sustaining more than a teraFLOPS on a wide range of DGEMM operations. Intel emphasized during the demonstration that this was a sustained teraFLOPS (non "raw teraFLOPS" used past others to get college but less meaningful numbers), and that information technology was the beginning general purpose processor to e'er cross a teraFLOPS.[48] [49]

On June xviii, 2012, IBM's Sequoia supercomputer system, based at the U.S. Lawrence Livermore National Laboratory (LLNL), reached xvi petaFLOPS, setting the world record and claiming first identify in the latest TOP500 list.[50]

On November 12, 2012, the TOP500 list certified Titan as the world'due south fastest supercomputer per the LINPACK benchmark, at 17.59 petaFLOPS.[51] [52] Information technology 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.[53] [54]

On June 10, 2013, Mainland china's Tianhe-ii was ranked the world's fastest with 33.86 petaFLOPS.[55]

On June twenty, 2016, China'southward Sunway TaihuLight was ranked the world'due south fastest with 93 petaFLOPS on the LINPACK benchmark (out of 125 acme petaFLOPS). The arrangement, which is almost exclusively based on engineering developed in China, is installed at the National Supercomputing Center in Wuxi, and represents more performance than the next five most powerful systems on the TOP500 list combined.[56]

In June 2019, Height, an IBM-built supercomputer now running at the Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL), captured the number one spot with a performance of 148.six petaFLOPS on High Functioning Linpack (HPL), the benchmark used to rank the TOP500 listing. Superlative has iv,356 nodes, each one equipped with 2 22-core Power9 CPUs, and vi NVIDIA Tesla V100 GPUs.[57]

In June 2020, Fugaku turned in a Loftier Performance Linpack (HPL) result of 415.5 petaFLOPS, besting the now 2nd-place Top system past a factor of ii.8x. Fugaku is powered by Fujitsu's 48-cadre A64FX SoC, becoming the start number one arrangement on the list to exist powered by ARM processors. In single or further reduced precision, used in machine learning and AI applications, Fugaku'due south peak performance is over i,000 petaflops (1 exaflops). The new system is installed at RIKEN Centre for Computational Science (R-CCS) in Kobe, Nippon.[ citation needed ]

Distributed calculating records [edit]

Distributed computing uses the Internet to link personal computers to achieve more FLOPS:

  • Equally of Apr 2020[update], the Folding@home network has over 2.3 exaFLOPS of total computing power.[58] [59] [lx] [61] It is the virtually powerful distributed computer network, being the first ever to interruption one exaFLOPS of full computing power. This level of functioning is primarily enabled by the cumulative effort of a vast array of powerful GPU and CPU units.[62]
  • Every bit of December 2020[update], the unabridged BOINC network averages about 31 petaFLOPS.[63]
  • As of June 2018[update], SETI@Habitation, employing the BOINC software platform, averages 896 teraFLOPS.[64]
  • As of June 2018[update], Einstein@Abode, a project using the BOINC network, is crunching at iii petaFLOPS.[65]
  • As of June 2018[update], MilkyWay@Home, using the BOINC infrastructure, computes at 847 teraFLOPS.[66]
  • As of June 2020[update], GIMPS, searching for Mersenne primes, is sustaining 1,354 teraFLOPS.[67]

Price of calculating [edit]

Hardware costs [edit]

Date Approximate USD per GFLOPS Platform providing the lowest cost per GFLOPS Comments
Unadjusted 2020[68]
1945 $129.49 trillion $i.88 quadrillion ENIAC: $487,000 in 1945 and $7,195,000 in 2019 $487,000 / 0.0000000385 GFLOPS
1961 $18.7 billion $161.9 billion A basic installation of IBM 7030 Stretch had a cost at the time of U.s.$7.78 million each. The IBM 7030 Stretch performs one floating-betoken multiply every 2.iv microseconds.[69]
1984 $18,750,000 $46,710,000 Cray X-MP/48 $15,000,000 / 0.viii GFLOPS
1997 $30,000 $48,000 2 16-processor Beowulf clusters with Pentium Pro microprocessors[70]
Apr 2000 $i,000 $1,530 Bunyip Beowulf cluster Bunyip was the first sub-US$1/MFLOPS computing engineering. It won the Gordon Bong Prize in 2000.
May 2000 $640 $975 KLAT2 KLAT2 was the offset computing technology which scaled to large applications while staying under Us-$1/MFLOPS.[71]
Baronial 2003 $82 $115 KASY0 KASY0 was the first sub-US$100/GFLOPS computing technology.[72]
August 2007 $48 $60 Microwulf As of August 2007, this 26.25 GFLOPS "personal" Beowulf cluster can be built for $1256.[73]
March 2011 $1.80 $2.09 HPU4Science This $30,000 cluster was built using only commercially bachelor "gamer" grade hardware.[74]
Baronial 2012 $0.75 $0.85 Quad AMD Radeon 7970 GHz System A quad AMD Radeon 7970 desktop computer reaching 16 TFLOPS of single-precision, four TFLOPS of double-precision computing operation. Total arrangement price was $3000; built using merely commercially bachelor hardware.[75]
June 2013 $0.22 $0.24 Sony PlayStation iv The Sony PlayStation four is listed every bit having a height functioning of 1.84 TFLOPS, at a price of $400[76]
November 2013 $0.16 $0.18 AMD Sempron 145 & GeForce GTX 760 Organisation Congenital using commercially bachelor parts, a system using 1 AMD Sempron 145 and three Nvidia GeForce GTX 760 reaches a total of 6.771 TFLOPS for a total cost of $1090.66.[77]
December 2013 $0.12 $0.13 Pentium G550 & Radeon R9 290 System Congenital using commercially available parts. Intel Pentium G550 and AMD Radeon R9 290 tops out at 4.848 TFLOPS g full of US$681.84.[78]
January 2015 $0.08 $0.09 Celeron G1830 & Radeon R9 295X2 System Built using commercially available parts. Intel Celeron G1830 and AMD Radeon R9 295X2 tops out at over 11.5 TFLOPS at a thou total of U.s.$902.57.[79] [lxxx]
June 2017 $0.06 $0.06 AMD Ryzen 7 1700 & AMD Radeon Vega Frontier Edition Built using commercially available parts. AMD Ryzen 7 1700 CPU combined with AMD Radeon Vega Iron cards in CrossFire tops out at over 50 TFLOPS at just under US$3,000 for the consummate system.[81]
October 2017 $0.03 $0.03 Intel Celeron G3930 & AMD RX Vega 64 Built using commercially bachelor parts. Three AMD RX Vega 64 graphics cards provide just over 75 TFLOPS half precision (38 TFLOPS SP or 2.6 TFLOPS DP when combined with the CPU) at ~$2,050 for the consummate system.[82]
Nov 2020 $0.03 $0.03 AMD Ryzen 3600 & 3× NVIDIA RTX 3080 AMD Ryzen 3600 @ 484 GFLOPS & $199.99

three× NVIDIA RTX 3080 @ 29,770 GFLOPS each & $699.99

Total organization GFLOPS = 89,794 / TFLOPS= 89.2794

Total organisation toll incl. realistic only depression cost parts; matched with other example = $2839[83]

US$/GFLOP = $0.0314

November 2020 $0.04 $0.04 PlayStation five The Sony PlayStation 5 digital edition is listed as having a peak performance of 10.28 TFLOPS (20.58 TFLOPS half precision) at a retail price of $399.[84]
November 2020 $0.04 $0.04 Xbox Series 10 Microsoft'south Xbox Series X is listed as having a elevation performance of 12.fifteen TFLOPS at a retail price of $499.[85]

Run across also [edit]

  • Computer functioning by orders of magnitude
  • Gordon Bong Prize
  • LINPACK benchmarks
  • Moore's law
  • Multiply–accrue operation
  • Functioning per watt#FLOPS per watt
  • Exaflop calculating
  • SPECfp
  • SPECint
  • SUPS
  • TOP500

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Source: https://en.wikipedia.org/wiki/FLOPS

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