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Wikipedia

FLOPS

April 04, 2023

For other uses, see Flop.
"Operations per second" redirects here. Not to be confused with Instructions per second.

Computer performance
Name Unit Value
kiloFLOPS kFLOPS 103
megaFLOPS MFLOPS 106
gigaFLOPS GFLOPS 109
teraFLOPS TFLOPS 1012
petaFLOPS PFLOPS 1015
exaFLOPS EFLOPS 1018
zettaFLOPS ZFLOPS 1021
yottaFLOPS YFLOPS 1024
ronnaFLOPS RFLOPS 1027
quettaFLOPS QFLOPS 1030

In computing, floating point operations per second (FLOPS, flops or flop/s) is a measure of computer performance, useful in fields of scientific computations that require floating-point calculations. For such cases, it is a more accurate measure than measuring instructions per second.

FLOPS by the largest supercomputer over time

Floating-point arithmetic

Floating-point arithmetic is needed for very large or very small real numbers, or computations that require a large dynamic range. Floating-point representation is similar to scientific notation, except everything is carried out in base two, rather than base ten. The encoding scheme stores the sign, the exponent (in base two for Cray and VAX, base two or ten for IEEE floating point formats, and base 16 for IBM Floating Point Architecture) and the significand (number after the radix point). While several similar formats are in use, the most common is ANSI/IEEE Std. 754-1985. This standard defines the format for 32-bit numbers called single precision, as well as 64-bit numbers called double precision and longer numbers called extended precision (used for intermediate results). Floating-point representations can support a much wider range of values than fixed-point, with the ability to represent very small numbers and very large numbers.[1]

Dynamic range and precision

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

Computational performance

FLOPS and MIPS are units of measure for the numerical computing performance of a computer. Floating-point operations are typically used in fields such as scientific computational research. The unit MIPS measures integer performance of a computer. Examples of integer operation include data movement (A to B) or value testing (If A = B, then C). MIPS as a performance benchmark is adequate when a computer is used in database queries, word processing, spreadsheets, or to run multiple virtual operating systems.[3][4] Frank H. McMahon, of the Lawrence Livermore National Laboratory, invented the terms FLOPS and MFLOPS (megaFLOPS) so that he could compare the supercomputers of the day by the number of floating-point calculations they performed per second.[citation needed] This was much better than using the prevalent MIPS to compare computers as this statistic usually had little bearing on the arithmetic capability of the machine.

FLOPS on an HPC-system can be calculated using this equation:[5]

 

This can be simplified to the most common case: a computer that has exactly 1 CPU:

 

FLOPS can be recorded in different measures of precision, for example, the TOP500 supercomputer list ranks computers by 64 bit (double-precision floating-point format) operations per second, abbreviated to FP64.[6] Similar measures are available for 32-bit (FP32) and 16-bit (FP16) operations.

Floating-point operations per clock cycle for various processors

Floating-point operations per clock cycle per core[7]
Microarchitecture ISA FP64 FP32 FP16
Intel CPU
Intel 80486 x87 (32-bit) ? 0.128[8] ?
x87 (32-bit) ? 0.5[8] ?
MMX (64-bit) ? 1[9] ?
Intel P6 Pentium III SSE (64-bit) ? 2[9] ?
Intel NetBurst Pentium 4 (Willamette, Northwood) SSE2 (64-bit) 2 4 ?
Intel P6 Pentium M SSE2 (64-bit) 1 2 ?
SSE3 (64-bit) 2 4 ?
4 8 ?
Intel Atom (Bonnell, Saltwell, Silvermont and Goldmont) SSE3 (128-bit) 2 4 ?
Intel Sandy Bridge (Sandy Bridge, Ivy Bridge) AVX (256-bit) 8 16 0
AVX2 & FMA (256-bit) 16 32 0
Intel Xeon Phi (Knights Corner) IMCI (512-bit) 16 32 0
AVX-512 & FMA (512-bit) 32 64 0
AMD CPU
AMD Bobcat AMD64 (64-bit) 2 4 0
4 8 0
AMD K10 SSE4/4a (128-bit) 4 8 0
AMD Bulldozer[10] (Piledriver, Steamroller, Excavator)
  • AVX (128-bit) Bulldozer-Steamroller
  • AVX2 (128-bit) Excavator
  • FMA3 (Bulldozer)[11]
  • FMA3/4 (Piledriver-Excavator)
 4 8 0
AVX2 & FMA (128-bit, 256-bit decoding)[15] 8 16 0
AVX2 & FMA (256-bit) 16 32 0
ARM CPU
ARM Cortex-A7, A9, A15 ARMv7 1 8 0
ARM Cortex-A32, A35, A53, A55, A72, A73, A75 ARMv8 2 8 0
ARM Cortex-A57[10] ARMv8 4 8 0
ARM Cortex-A76, A77, A78 ARMv8 8 16 0
ARM Cortex-X1 ARMv8 16 32 ?
Qualcomm Krait ARMv8 1 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 (Blue Gene/Q) ? 8 8 (as FP64) 0
Hitachi SH-4[17][18] SH-4 1 7 0
Nvidia GPU
Nvidia Curie (GeForce 6 series and GeForce 7 series) PTX ? 8 ?
Nvidia Tesla 2.0 (GeForce GTX 260–295) PTX ? 2 ?
Nvidia Fermi (only GeForce GTX 465–480, 560 Ti, 570–590) PTX 1/4 (locked by driver, 1 in hardware) 2 0
Nvidia Fermi (only Quadro 600–2000) PTX 1/8 2 0
Nvidia Fermi (only Quadro 4000–7000, Tesla) PTX 1 2 0
Nvidia Kepler (GeForce (except Titan and Titan Black), Quadro (except K6000), Tesla K10) PTX 1/12 (for GK110: locked by driver, 2/3 in hardware) 2 0
Nvidia Kepler (GeForce GTX Titan and Titan Black, Quadro K6000, Tesla (except K10)) PTX 2/3 2 0
  • Nvidia Maxwell
  • Nvidia Pascal (all except Quadro GP100 and Tesla P100)
 PTX 1/16 2 1/32
Nvidia Pascal (only Quadro GP100 and Tesla P100) PTX 1 2 4
Nvidia Volta[19] PTX 1 2 (FP32) + 2 (INT32) 16
Nvidia Turing (only GeForce 16XX) PTX 1/16 2 (FP32) + 2 (INT32) 4
Nvidia Turing (all except GeForce 16XX) PTX 1/16 2 (FP32) + 2 (INT32) 16
Nvidia Ampere[20][21] (only Tesla A100/A30) PTX 2 2 (FP32) + 2 (INT32) 32
Nvidia Ampere (all GeForce and Quadro, Tesla A40/A10) PTX 1/32 2 (FP32) + 0 (INT32) or 1 (FP32) + 1 (INT32) 8
AMD GPU
AMD TeraScale 1 (Radeon HD 4000 series) TeraScale 1 0.4 2 ?
AMD TeraScale 2 (Radeon HD 5000 series) TeraScale 2 1 2 ?
AMD TeraScale 3 (Radeon HD 6000 series) TeraScale 3 1 4 ?
AMD GCN (only Radeon Pro W 8100–9100) GCN 1 2 ?
AMD GCN (all except Radeon Pro W 8100–9100, Vega 10–20) GCN 1/8 2 4
AMD GCN Vega 10 GCN 1/8 2 4
AMD GCN Vega 20 (only Radeon VII) GCN 1/2 (locked by driver, 1 in hardware) 2 4
AMD GCN Vega 20 (only Radeon Instinct MI50 / MI60 and Radeon Pro VII) GCN 1 2 4
RDNA 1/8 2 4
AMD RDNA3 RDNA 1/8? 4 8?
AMD CDNA CDNA 1 4 (Tensor)[24] 16
AMD CDNA 2 CDNA 2 4 (Tensor) 4 (Tensor) 16
Intel GPU
Intel Xe-LP (Iris Xe MAX)[25] Xe 1/2? 2 4
Intel Xe-HPG (Arc Alchemist)[25] Xe 0 2 16
Intel Xe-HPC (Ponte Vecchio)[26] Xe 2 2 32
Qualcomm GPU
Qualcomm Adreno 5x0 Adreno 5xx 1 2 4
Qualcomm Adreno 6x0 Adreno 6xx 1 2 4
Graphcore
Graphcore Colossus GC2[27][28] ? 0 16 64
  • Graphcore Colossus GC200 Mk2[29]
  • Graphcore Bow-2000[30]
 ? 0 32 128
Supercomputer
ENIAC @ 100 kHz with 385 Flops[31]
48-bit processor @ 208 kHz in CDC 1604 in 1960
60-bit processor @ 10 MHz in CDC6600 in 1964 0.3 (FP60)
60-bit processor @ 10 MHz in CDC7600 in 1967 1.0 (FP60)
Cray-1 @ 80 MHz in 1976 2
CDC Cyber 205 @ 50 MHz in 1981 FORTRAN compiler

(ANSI 77 with vector extensions)

8 16
Microarchitecture ISA FP64 FP32 FP16

Performance records

Single computer records

In June 1997, Intel's ASCI Red was the world's first computer to achieve one teraFLOPS and beyond. Sandia director Bill Camp said that ASCI Red had the best reliability of any supercomputer ever built, and "was supercomputing's high-water mark in longevity, price, and performance".[32]

NEC's SX-9 supercomputer was the world's first vector processor to exceed 100 gigaFLOPS per single core.

In June 2006, a new computer was announced by Japanese research institute RIKEN, the MDGRAPE-3. The computer's performance tops out at one petaFLOPS, almost two times faster than the Blue Gene/L, but MDGRAPE-3 is not a general purpose computer, which is why it does not 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 3.13 GHz. The 80-core chip can raise this result to 2 teraFLOPS at 6.26 GHz, although the thermal dissipation at this frequency exceeds 190 watts.[33]

In June 2007, Top500.org reported the fastest computer in the world to be the IBM Blue Gene/L supercomputer, measuring a peak of 596 teraFLOPS.[34] The Cray XT4 hit second place with 101.7 teraFLOPS.

On June 26, 2007, IBM announced the second generation of its top supercomputer, dubbed Blue Gene/P and designed to continuously operate at speeds exceeding one petaFLOPS, faster than the Blue Gene/L. When configured to do so, it can reach speeds in excess of three petaFLOPS.[35]

On October 25, 2007, NEC Corporation of Japan issued a press release announcing its SX series model SX-9,[36] claiming it to be the world's fastest vector supercomputer. The SX-9 features the first CPU capable of a peak vector performance of 102.4 gigaFLOPS per single core.

On February 4, 2008, the NSF and the University of Texas at Austin opened full scale research runs on an AMD, Sun supercomputer named Ranger,[37] the most powerful supercomputing system in the world for open science research, 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 one petaFLOPS. It headed the June 2008 and November 2008 TOP500 list of the most powerful supercomputers (excluding grid computers).[38][39] The computer is located at Los Alamos National Laboratory in New Mexico. The computer's name refers to the New Mexico state bird, the greater roadrunner (Geococcyx californianus).[40]

In June 2008, AMD released ATI Radeon HD 4800 series, which are reported to be the first GPUs to achieve one teraFLOPS. On August 12, 2008, AMD released the ATI Radeon HD 4870X2 graphics card with two Radeon R770 GPUs totaling 2.4 teraFLOPS.

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

In 2009, the Cray Jaguar performed at 1.75 petaFLOPS, beating the IBM Roadrunner for the number one spot on the TOP500 list.[41]

In October 2010, China unveiled the Tianhe-1, a supercomputer that operates at a peak computing rate of 2.5 petaFLOPS.[42][43]

As of 2010 the fastest PC processor reached 109 gigaFLOPS (Intel Core i7 980 XE)[44] in double precision calculations. GPUs are considerably more powerful. For example, Nvidia Tesla C2050 GPU computing processors perform around 515 gigaFLOPS[45] in double precision calculations, and the AMD FireStream 9270 peaks at 240 gigaFLOPS.[46]

In November 2011, it was announced that Japan had achieved 10.51 petaFLOPS with its K computer.[47] It has 88,128 SPARC64 VIIIfx processors in 864 racks, with theoretical performance of 11.28 petaFLOPS. It is named after the Japanese word "kei", which stands for 10 quadrillion,[48] corresponding to the target speed of 10 petaFLOPS.

On November 15, 2011, Intel demonstrated a single 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 (not "raw teraFLOPS" used by others to get higher but less meaningful numbers), and that it was the first general purpose processor to ever cross a teraFLOPS.[49][50]

On June 18, 2012, IBM's Sequoia supercomputer system, based at the U.S. Lawrence Livermore National Laboratory (LLNL), reached 16 petaFLOPS, setting the world record and claiming first place in the latest TOP500 list.[51]

On November 12, 2012, the TOP500 list certified Titan as the world's fastest supercomputer per the LINPACK benchmark, at 17.59 petaFLOPS.[52][53] It 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.[54][55]

On June 10, 2013, China's Tianhe-2 was ranked the world's fastest with 33.86 petaFLOPS.[56]

On June 20, 2016, China's Sunway TaihuLight was ranked the world's fastest with 93 petaFLOPS on the LINPACK benchmark (out of 125 peak petaFLOPS). The system, which is almost exclusively based on technology 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.[57]

In June 2019, Summit, 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 148.6 petaFLOPS on High Performance Linpack (HPL), the benchmark used to rank the TOP500 list. Summit has 4,356 nodes, each one equipped with two 22-core Power9 CPUs, and six NVIDIA Tesla V100 GPUs.[58]

Distributed computing records

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

  • As of April 2020, the Folding@home network has over 2.3 exaFLOPS of total computing power.[59][60][61][62] It is the most powerful distributed computer network, being the first ever to break 1 exaFLOPS of total computing power. This level of performance is primarily enabled by the cumulative effort of a vast array of powerful GPU and CPU units.[63]
  • As of December 2020, the entire BOINC network averages about 31 petaFLOPS.[64]
  • As of June 2018, SETI@home, employing the BOINC software platform, averages 896 teraFLOPS.[65]
  • As of June 2018, Einstein@Home, a project using the BOINC network, is crunching at 3 petaFLOPS.[66]
  • As of June 2018, MilkyWay@home, using the BOINC infrastructure, computes at 847 teraFLOPS.[67]
  • As of June 2020, GIMPS, searching for Mersenne primes, is sustaining 1,354 teraFLOPS.[68]

Cost of computing

Hardware costs

Date Approximate USD per GFLOPS Platform providing the lowest cost per GFLOPS Comments
Unadjusted 2021[69]
1945 $129.49 trillion $1.88 quadrillion ENIAC: $487,000 in 1945 and $7,195,000 in 2019 $487,000 / 0.0000000385 GFLOPS
1961 $18.7 billion $169.6 billion A basic installation of IBM 7030 Stretch had a cost at the time of US$7.78 million each. The IBM 7030 Stretch performs one floating-point multiply every 2.4 microseconds.[70]
1984 $18,750,000 $48,900,000 Cray X-MP/48 $15,000,000 / 0.8 GFLOPS
1997 $30,000 $51,000 Two 16-processor Beowulf clusters with Pentium Pro microprocessors[71]
April 2000 $1,000 $1,600 Bunyip Beowulf cluster Bunyip was the first sub-US$1/MFLOPS computing technology. It won the Gordon Bell Prize in 2000.
May 2000 $640 $1,021 KLAT2 KLAT2 was the first computing technology which scaled to large applications while staying under US$1/MFLOPS.[72]
August 2003 $82 $121 KASY0 KASY0 was the first sub-US$100/GFLOPS computing technology.[73]
August 2007 $48 $63 Microwulf As of August 2007, this 26.25 GFLOPS "personal" Beowulf cluster can be built for $1256.[74]
March 2011 $1.80 $2.19 HPU4Science This $30,000 cluster was built using only commercially available "gamer" grade hardware.[75]
August 2012 $0.75 $0.89 Quad AMD Radeon 7970 System A quad AMD Radeon 7970 desktop computer reaching 16 TFLOPS of single-precision, 4 TFLOPS of double-precision computing performance. Total system cost was $3000; built using only commercially available hardware.[76]
June 2013 $0.22 $0.26 Sony PlayStation 4 The Sony PlayStation 4 is listed as having a peak performance of 1.84 TFLOPS, at a price of $400[77]
November 2013 $0.16 $0.19 AMD Sempron 145 & GeForce GTX 760 system Built using commercially available parts, a system using one AMD Sempron 145 and three Nvidia GeForce GTX 760 reaches a total of 6.771 TFLOPS for a total cost of US$1,090.66.[78]
December 2013 $0.12 $0.14 Pentium G550 & Radeon R9 290 system Built using commercially available parts. Intel Pentium G550 and AMD Radeon R9 290 tops out at 4.848 TFLOPS grand total of US$681.84.[79]
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 grand total of US$902.57.[80][81]
June 2017 $0.06 $0.07 AMD Ryzen 7 1700 & AMD Radeon Vega Frontier Edition system Built using commercially available parts. AMD Ryzen 7 1700 CPU combined with AMD Radeon Vega FE cards in CrossFire tops out at over 50 TFLOPS at just under US$3,000 for the complete system.[82]
October 2017 $0.03 $0.03 Intel Celeron G3930 & AMD RX Vega 64 system Built using commercially available 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 complete system.[83]
November 2020 $0.03 $0.03 AMD Ryzen 3600 & 3× NVIDIA RTX 3080 system AMD Ryzen 3600 @ 484 GFLOPS & $199.99

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

Total system GFLOPS = 89,794 / TFLOPS= 89.2794

Total system cost incl. realistic but low cost parts; matched with other example = $2839[84]

US$/GFLOP = $0.0314

November 2020 $0.04 $0.04 PlayStation 5 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.[85]
November 2020 $0.04 $0.04 Xbox Series X Microsoft's Xbox Series X is listed as having a peak performance of 12.15 TFLOPS (24.30 TFLOPS half precision) at a retail price of $499.[86]
September 2022 $0.02 $0.02 RTX 4090 Nvidia's RTX 4090 is listed as having a peak performance of 82.6 TFLOPS (1321 Tensor TFLOPS) at a retail price of $1599.[87]


See also

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April 04, 2023
flops, other, uses, flop, operations, second, redirects, here, confused, with, instructions, second, this, article, needs, additional, citations, verification, please, help, improve, this, article, adding, citations, reliable, sources, unsourced, material, cha. For other uses see Flop Operations per second redirects here Not to be confused with Instructions per second This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources FLOPS news newspapers books scholar JSTOR February 2015 Learn how and when to remove this template message Computer performance Name Unit ValuekiloFLOPS kFLOPS 103megaFLOPS MFLOPS 106gigaFLOPS GFLOPS 109teraFLOPS TFLOPS 1012petaFLOPS PFLOPS 1015exaFLOPS EFLOPS 1018zettaFLOPS ZFLOPS 1021yottaFLOPS YFLOPS 1024ronnaFLOPS RFLOPS 1027quettaFLOPS QFLOPS 1030In computing floating point operations per second FLOPS flops or flop s is a measure of computer performance useful in fields of scientific computations that require floating point calculations For such cases it is a more accurate measure than measuring instructions per second FLOPS by the largest supercomputer over time Contents 1 Floating point arithmetic 1 1 Dynamic range and precision 1 2 Computational performance 2 Floating point operations per clock cycle for various processors 3 Performance records 3 1 Single computer records 3 2 Distributed computing records 4 Cost of computing 4 1 Hardware costs 5 See also 6 ReferencesFloating point arithmetic EditFloating point arithmetic is needed for very large or very small real numbers or computations that require a large dynamic range Floating point representation is similar to scientific notation except everything is carried out in base two rather than base ten The encoding scheme stores the sign the exponent in base two for Cray and VAX base two or ten for IEEE floating point formats and base 16 for IBM Floating Point Architecture and the significand number after the radix point While several similar formats are in use the most common is ANSI IEEE Std 754 1985 This standard defines the format for 32 bit numbers called single precision as well as 64 bit numbers called double precision and longer numbers called extended precision used for intermediate results Floating point representations can support a much wider range of values than fixed point with the ability to represent very small numbers and very large numbers 1 Dynamic range and precision Edit The exponentiation inherent in floating point computation assures a much larger dynamic range the largest and smallest numbers that can be represented which is especially important when processing data sets where some of the data may have extremely large range of numerical values or where the range may be unpredictable As such floating point processors are ideally suited for computationally intensive applications 2 Computational performance Edit FLOPS and MIPS are units of measure for the numerical computing performance of a computer Floating point operations are typically used in fields such as scientific computational research The unit MIPS measures integer performance of a computer Examples of integer operation include data movement A to B or value testing If A B then C MIPS as a performance benchmark is adequate when a computer is used in database queries word processing spreadsheets or to run multiple virtual operating systems 3 4 Frank H McMahon of the Lawrence Livermore National Laboratory invented the terms FLOPS and MFLOPS megaFLOPS so that he could compare the supercomputers of the day by the number of floating point calculations they performed per second citation needed This was much better than using the prevalent MIPS to compare computers as this statistic usually had little bearing on the arithmetic capability of the machine FLOPS on an HPC system can be calculated using this equation 5 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 second times frac text FLOPs text cycle This can be simplified to the most common case a computer that has exactly 1 CPU FLOPS cores cycles second 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 example the TOP500 supercomputer list ranks computers by 64 bit double precision floating point format operations per second abbreviated to FP64 6 Similar measures are available for 32 bit FP32 and 16 bit FP16 operations Floating point operations per clock cycle for various processors EditFloating point operations per clock cycle per core 7 Microarchitecture ISA FP64 FP32 FP16Intel CPUIntel 80486 x87 32 bit 0 128 8 Intel P5 Pentium Intel P6 Pentium Pro x87 32 bit 0 5 8 Intel P5 Pentium MMX Intel P6 Pentium II MMX 64 bit 1 9 Intel P6 Pentium III SSE 64 bit 2 9 Intel NetBurst Pentium 4 Willamette Northwood SSE2 64 bit 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 4 Intel Core Merom Penryn Intel Nehalem 10 Nehalem Westmere SSSE3 128 bit SSE4 128 bit 4 8 Intel Atom Bonnell Saltwell Silvermont and Goldmont SSE3 128 bit 2 4 Intel Sandy Bridge Sandy Bridge Ivy Bridge AVX 256 bit 8 16 0Intel Haswell 10 Haswell Devil s Canyon Broadwell Intel Skylake Skylake Kaby Lake Coffee Lake Comet Lake Whiskey Lake Amber Lake AVX2 amp FMA 256 bit 16 32 0Intel Xeon Phi Knights Corner IMCI 512 bit 16 32 0Intel Skylake X Skylake X Cascade Lake Intel Xeon Phi Knights Landing Knights Mill Intel Ice Lake Tiger Lake and Rocket Lake AVX 512 amp FMA 512 bit 32 64 0AMD CPUAMD Bobcat AMD64 64 bit 2 4 0AMD Jaguar AMD Puma 4 8 0AMD K10 SSE4 4a 128 bit 4 8 0AMD Bulldozer 10 Piledriver Steamroller Excavator AVX 128 bit Bulldozer Steamroller AVX2 128 bit Excavator FMA3 Bulldozer 11 FMA3 4 Piledriver Excavator 4 8 0AMD Zen Ryzen 1000 series Threadripper 1000 series Epyc Naples AMD Zen 10 12 13 14 Ryzen 2000 series Threadripper 2000 series AVX2 amp FMA 128 bit 256 bit decoding 15 8 16 0AMD Zen 2 16 Ryzen 3000 series Threadripper 3000 series Epyc Rome AMD Zen 3 Ryzen 5000 series Epyc Milan AVX2 amp FMA 256 bit 16 32 0ARM CPUARM Cortex A7 A9 A15 ARMv7 1 8 0ARM Cortex A32 A35 A53 A55 A72 A73 A75 ARMv8 2 8 0ARM Cortex A57 10 ARMv8 4 8 0ARM Cortex A76 A77 A78 ARMv8 8 16 0ARM Cortex X1 ARMv8 16 32 Qualcomm Krait ARMv8 1 8 0Qualcomm Kryo 1xx 3xx ARMv8 2 8 0Qualcomm Kryo 4xx 5xx ARMv8 8 16 0Samsung Exynos M1 and M2 ARMv8 2 8 0Samsung Exynos M3 and M4 ARMv8 3 12 0IBM PowerPC A2 Blue Gene Q 8 8 as FP64 0Hitachi SH 4 17 18 SH 4 1 7 0Nvidia GPUNvidia Curie GeForce 6 series and GeForce 7 series PTX 8 Nvidia Tesla 2 0 GeForce GTX 260 295 PTX 2 Nvidia Fermi only GeForce GTX 465 480 560 Ti 570 590 PTX 1 4 locked by driver 1 in hardware 2 0Nvidia Fermi only Quadro 600 2000 PTX 1 8 2 0Nvidia Fermi only Quadro 4000 7000 Tesla PTX 1 2 0Nvidia Kepler GeForce except Titan and Titan Black Quadro except K6000 Tesla K10 PTX 1 12 for GK110 locked by driver 2 3 in hardware 2 0Nvidia Kepler GeForce GTX Titan and Titan Black Quadro K6000 Tesla except K10 PTX 2 3 2 0Nvidia Maxwell Nvidia Pascal all except Quadro GP100 and Tesla P100 PTX 1 16 2 1 32Nvidia Pascal only Quadro GP100 and Tesla P100 PTX 1 2 4Nvidia Volta 19 PTX 1 2 FP32 2 INT32 16Nvidia Turing only GeForce 16XX PTX 1 16 2 FP32 2 INT32 4Nvidia Turing all except GeForce 16XX PTX 1 16 2 FP32 2 INT32 16Nvidia Ampere 20 21 only Tesla A100 A30 PTX 2 2 FP32 2 INT32 32Nvidia Ampere all GeForce and Quadro Tesla A40 A10 PTX 1 32 2 FP32 0 INT32 or 1 FP32 1 INT32 8AMD GPUAMD TeraScale 1 Radeon HD 4000 series TeraScale 1 0 4 2 AMD TeraScale 2 Radeon HD 5000 series TeraScale 2 1 2 AMD TeraScale 3 Radeon HD 6000 series TeraScale 3 1 4 AMD GCN only Radeon Pro W 8100 9100 GCN 1 2 AMD GCN all except Radeon Pro W 8100 9100 Vega 10 20 GCN 1 8 2 4AMD GCN Vega 10 GCN 1 8 2 4AMD GCN Vega 20 only Radeon VII GCN 1 2 locked by driver 1 in hardware 2 4AMD GCN Vega 20 only Radeon Instinct MI50 MI60 and Radeon Pro VII GCN 1 2 4AMD RDNA 22 23 AMD RDNA 2 RDNA 1 8 2 4AMD RDNA3 RDNA 1 8 4 8 AMD CDNA CDNA 1 4 Tensor 24 16AMD CDNA 2 CDNA 2 4 Tensor 4 Tensor 16Intel GPUIntel Xe LP Iris Xe MAX 25 Xe 1 2 2 4Intel Xe HPG Arc Alchemist 25 Xe 0 2 16Intel Xe HPC Ponte Vecchio 26 Xe 2 2 32Qualcomm GPUQualcomm Adreno 5x0 Adreno 5xx 1 2 4Qualcomm Adreno 6x0 Adreno 6xx 1 2 4GraphcoreGraphcore Colossus GC2 27 28 0 16 64Graphcore Colossus GC200 Mk2 29 Graphcore Bow 2000 30 0 32 128SupercomputerENIAC 100 kHz with 385 Flops 31 48 bit processor 208 kHz in CDC 1604 in 196060 bit processor 10 MHz in CDC6600 in 1964 0 3 FP60 60 bit processor 10 MHz in CDC7600 in 1967 1 0 FP60 Cray 1 80 MHz in 1976 2CDC Cyber 205 50 MHz in 1981 FORTRAN compiler ANSI 77 with vector extensions 8 16Microarchitecture ISA FP64 FP32 FP16Performance records EditSingle computer records Edit In June 1997 Intel s ASCI Red was the world s first computer to achieve one teraFLOPS and beyond Sandia director Bill Camp said that ASCI Red had the best reliability of any supercomputer ever built and was supercomputing s high water mark in longevity price and performance 32 NEC s SX 9 supercomputer was the world s first vector processor to exceed 100 gigaFLOPS per single core In June 2006 a new computer was announced by Japanese research institute RIKEN the MDGRAPE 3 The computer s performance tops out at one petaFLOPS almost two times faster than the Blue Gene L but MDGRAPE 3 is not a general purpose computer which is why it does not 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 3 13 GHz The 80 core chip can raise this result to 2 teraFLOPS at 6 26 GHz although the thermal dissipation at this frequency exceeds 190 watts 33 In June 2007 Top500 org reported the fastest computer in the world to be the IBM Blue Gene L supercomputer measuring a peak of 596 teraFLOPS 34 The Cray XT4 hit second place with 101 7 teraFLOPS On June 26 2007 IBM announced the second generation of its top supercomputer dubbed Blue Gene P and designed to continuously operate at speeds exceeding one petaFLOPS faster than the Blue Gene L When configured to do so it can reach speeds in excess of three petaFLOPS 35 On October 25 2007 NEC Corporation of Japan issued a press release announcing its SX series model SX 9 36 claiming it to be the world s fastest vector supercomputer The SX 9 features the first CPU capable of a peak vector performance of 102 4 gigaFLOPS per single core On February 4 2008 the NSF and the University of Texas at Austin opened full scale research runs on an AMD Sun supercomputer named Ranger 37 the most powerful supercomputing system in the world for open science research 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 one petaFLOPS It headed the June 2008 and November 2008 TOP500 list of the most powerful supercomputers excluding grid computers 38 39 The computer is located at Los Alamos National Laboratory in New Mexico The computer s name refers to the New Mexico state bird the greater roadrunner Geococcyx californianus 40 In June 2008 AMD released ATI Radeon HD 4800 series which are reported to be the first GPUs to achieve one teraFLOPS On August 12 2008 AMD released the ATI Radeon HD 4870X2 graphics card with two Radeon R770 GPUs totaling 2 4 teraFLOPS In November 2008 an upgrade to the Cray Jaguar supercomputer at the Department of Energy s DOE s Oak Ridge National Laboratory ORNL raised the system s computing power to a peak 1 64 petaFLOPS making Jaguar the world s first petaFLOPS system dedicated to open research In early 2009 the supercomputer was named after a mythical creature Kraken Kraken was declared the world s fastest university managed supercomputer and sixth fastest overall in the 2009 TOP500 list In 2010 Kraken was upgraded and can operate faster and is more powerful In 2009 the Cray Jaguar performed at 1 75 petaFLOPS beating the IBM Roadrunner for the number one spot on the TOP500 list 41 In October 2010 China unveiled the Tianhe 1 a supercomputer that operates at a peak computing rate of 2 5 petaFLOPS 42 43 As of 2010 update the fastest PC processor reached 109 gigaFLOPS Intel Core i7 980 XE 44 in double precision calculations GPUs are considerably more powerful For example Nvidia Tesla C2050 GPU computing processors perform around 515 gigaFLOPS 45 in double precision calculations and the AMD FireStream 9270 peaks at 240 gigaFLOPS 46 In November 2011 it was announced that Japan had achieved 10 51 petaFLOPS with its K computer 47 It has 88 128 SPARC64 VIIIfx processors in 864 racks with theoretical performance of 11 28 petaFLOPS It is named after the Japanese word kei which stands for 10 quadrillion 48 corresponding to the target speed of 10 petaFLOPS On November 15 2011 Intel demonstrated a single 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 not raw teraFLOPS used by others to get higher but less meaningful numbers and that it was the first general purpose processor to ever cross a teraFLOPS 49 50 On June 18 2012 IBM s Sequoia supercomputer system based at the U S Lawrence Livermore National Laboratory LLNL reached 16 petaFLOPS setting the world record and claiming first place in the latest TOP500 list 51 On November 12 2012 the TOP500 list certified Titan as the world s fastest supercomputer per the LINPACK benchmark at 17 59 petaFLOPS 52 53 It 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 54 55 On June 10 2013 China s Tianhe 2 was ranked the world s fastest with 33 86 petaFLOPS 56 On June 20 2016 China s Sunway TaihuLight was ranked the world s fastest with 93 petaFLOPS on the LINPACK benchmark out of 125 peak petaFLOPS The system which is almost exclusively based on technology 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 57 In June 2019 Summit 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 6 petaFLOPS on High Performance Linpack HPL the benchmark used to rank the TOP500 list Summit has 4 356 nodes each one equipped with two 22 core Power9 CPUs and six NVIDIA Tesla V100 GPUs 58 Distributed computing records Edit Distributed computing uses the Internet to link personal computers to achieve more FLOPS As of April 2020 update the Folding home network has over 2 3 exaFLOPS of total computing power 59 60 61 62 It is the most powerful distributed computer network being the first ever to break 1 exaFLOPS of total computing power This level of performance is primarily enabled by the cumulative effort of a vast array of powerful GPU and CPU units 63 As of December 2020 update the entire BOINC network averages about 31 petaFLOPS 64 As of June 2018 update SETI home employing the BOINC software platform averages 896 teraFLOPS 65 As of June 2018 update Einstein Home a project using the BOINC network is crunching at 3 petaFLOPS 66 As of June 2018 update MilkyWay home using the BOINC infrastructure computes at 847 teraFLOPS 67 As of June 2020 update GIMPS searching for Mersenne primes is sustaining 1 354 teraFLOPS 68 Cost of computing EditHardware costs Edit Date Approximate USD per GFLOPS Platform providing the lowest cost per GFLOPS CommentsUnadjusted 2021 69 1945 129 49 trillion 1 88 quadrillion ENIAC 487 000 in 1945 and 7 195 000 in 2019 487 000 0 000000 0385 GFLOPS1961 18 7 billion 169 6 billion A basic installation of IBM 7030 Stretch had a cost at the time of US 7 78 million each The IBM 7030 Stretch performs one floating point multiply every 2 4 microseconds 70 1984 18 750 000 48 900 000 Cray X MP 48 15 000 000 0 8 GFLOPS1997 30 000 51 000 Two 16 processor Beowulf clusters with Pentium Pro microprocessors 71 April 2000 1 000 1 600 Bunyip Beowulf cluster Bunyip was the first sub US 1 MFLOPS computing technology It won the Gordon Bell Prize in 2000 May 2000 640 1 021 KLAT2 KLAT2 was the first computing technology which scaled to large applications while staying under US 1 MFLOPS 72 August 2003 82 121 KASY0 KASY0 was the first sub US 100 GFLOPS computing technology 73 August 2007 48 63 Microwulf As of August 2007 this 26 25 GFLOPS personal Beowulf cluster can be built for 1256 74 March 2011 1 80 2 19 HPU4Science This 30 000 cluster was built using only commercially available gamer grade hardware 75 August 2012 0 75 0 89 Quad AMD Radeon 7970 System A quad AMD Radeon 7970 desktop computer reaching 16 TFLOPS of single precision 4 TFLOPS of double precision computing performance Total system cost was 3000 built using only commercially available hardware 76 June 2013 0 22 0 26 Sony PlayStation 4 The Sony PlayStation 4 is listed as having a peak performance of 1 84 TFLOPS at a price of 400 77 November 2013 0 16 0 19 AMD Sempron 145 amp GeForce GTX 760 system Built using commercially available parts a system using one AMD Sempron 145 and three Nvidia GeForce GTX 760 reaches a total of 6 771 TFLOPS for a total cost of US 1 090 66 78 December 2013 0 12 0 14 Pentium G550 amp Radeon R9 290 system Built using commercially available parts Intel Pentium G550 and AMD Radeon R9 290 tops out at 4 848 TFLOPS grand total of US 681 84 79 January 2015 0 08 0 09 Celeron G1830 amp 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 grand total of US 902 57 80 81 June 2017 0 06 0 07 AMD Ryzen 7 1700 amp AMD Radeon Vega Frontier Edition system Built using commercially available parts AMD Ryzen 7 1700 CPU combined with AMD Radeon Vega FE cards in CrossFire tops out at over 50 TFLOPS at just under US 3 000 for the complete system 82 October 2017 0 03 0 03 Intel Celeron G3930 amp AMD RX Vega 64 system Built using commercially available 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 complete system 83 November 2020 0 03 0 03 AMD Ryzen 3600 amp 3 NVIDIA RTX 3080 system AMD Ryzen 3600 484 GFLOPS amp 199 99 3 NVIDIA RTX 3080 29 770 GFLOPS each amp 699 99Total system GFLOPS 89 794 TFLOPS 89 2794Total system cost incl realistic but low cost parts matched with other example 2839 84 US GFLOP 0 0314November 2020 0 04 0 04 PlayStation 5 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 85 November 2020 0 04 0 04 Xbox Series X Microsoft s Xbox Series X is listed as having a peak performance of 12 15 TFLOPS 24 30 TFLOPS half precision at a retail price of 499 86 September 2022 0 02 0 02 RTX 4090 Nvidia s RTX 4090 is listed as having a peak performance of 82 6 TFLOPS 1321 Tensor TFLOPS at a retail price of 1599 87 See also EditComputer performance by orders of magnitude Gordon Bell Prize LINPACK benchmarks Moore s law Multiply accumulate operation Performance per watt FLOPS per watt Exascale computing SPECfp SPECint SUPS TOP500References Edit Floating Point Retrieved on December 25 2009 Summary Fixed point integer vs floating point Retrieved on December 25 2009 Fixed versus floating point Retrieved on December 25 2009 Data manipulation and math calculation Retrieved on December 25 2009 Nodes Sockets Cores and FLOPS Oh My by Dr Mark R Fernandez Ph D FREQUENTLY ASKED QUESTIONS top500 org Retrieved June 23 2020 Floating Point Operations Per Second FLOPS a b home iae nl a href Template Cite web html title Template Cite web cite web a CS1 maint url status link a b Computing Power throughout History alternatewars com Retrieved February 13 2021 a b c d e Dolbeau Romain 2017 Theoretical Peak FLOPS per instruction set a tutorial Journal of Supercomputing 74 3 1341 1377 doi 10 1007 s11227 017 2177 5 S2CID 3540951 New instructions support for Bulldozer FMA3 and Piledriver FMA3 4 and CVT BMI TBM PDF Agner s CPU blog Test results for AMD Ryzen https arstechnica com gadgets 2017 03 amds moment of zen finally an architecture that can compete 2 each core now has a pair of 128 bit FMA units of its own Mike Clark August 23 2016 A New x86 Core Architecture for the Next Generation of Computing PDF HotChips 28 AMD page 7 The microarchitecture of Intel and AMD CPUs PDF AMD CEO Lisa Su s COMPUTEX 2019 Keynote youtube com Archived from the original on December 11 2021 Entertainment Systems and High Performance Processor SH 4 PDF Hitachi Review Hitachi 48 2 58 63 1999 Retrieved June 21 2019 SH 4 Next Generation DSP Architecture for VoIP PDF Hitachi 2000 Retrieved June 21 2019 Inside Volta The World s Most Advanced Data Center GPU May 10 2017 NVIDIA Ampere Architecture In Depth May 14 2020 NVIDIA A100 GPUs Power the Modern Data Center NVIDIA Schilling Andreas Die RDNA Architektur Seite 2 Hardwareluxx AMD Radeon RX 5700 XT Specs TechPowerUp AMD Instinct MI100 Accelerator a b Introduction to the Xe HPG Architecture Intel Data Center GPU Max 250 TFLOPs s for two chips with FP16 mixed precision youtube com Archived at Ghostarchive and the Wayback Machine Estimation via power consumption that FP32 is 1 4 of FP16 and that clock frequency is below 1 5GHz youtube com Archived at Ghostarchive and the Wayback Machine Introducing Graphcore s Mk2 IPU systems youtube com Bow 2000 IPU Machine docs graphcore ai Computers of Yore clear rice edu Retrieved February 26 2021 Sandia s ASCI Red world s first teraflop supercomputer is decommissioned PDF Archived from the original PDF on November 5 2010 Retrieved November 17 2011 Richard Swinburne April 30 2007 The Arrival of TeraFLOP Computing bit tech net Retrieved February 9 2012 29th TOP500 List of World s Fastest Supercomputers Released Top500 org June 23 2007 Archived from the original on May 9 2008 Retrieved July 8 2008 June 2008 TOP500 Retrieved July 8 2008 NEC Launches World s Fastest Vector Supercomputer SX 9 NEC October 25 2007 Retrieved July 8 2008 University of Texas at Austin Texas Advanced Computing Center Archived from the original on August 1 2009 Retrieved September 13 2010 Any researcher at a U S institution can submit a proposal to request an allocation of cycles on the system Sharon Gaudin June 9 2008 IBM s Roadrunner smashes 4 minute mile of supercomputing Computerworld Archived from the original on December 24 2008 Retrieved June 10 2008 Austin ISC08 Top500 org November 14 2008 Archived from the original on February 22 2012 Retrieved February 9 2012 Fildes Jonathan June 9 2008 Supercomputer sets petaflop pace BBC News Retrieved July 8 2008 Greenberg Andy November 16 2009 Cray Dethrones IBM in Supercomputing Forbes China claims supercomputer crown BBC News October 28 2010 Dillow Clay October 28 2010 China Unveils 2507 Petaflop Supercomputer the World s Fastest Popsci com Retrieved February 9 2012 Intel s Core i7 980X Extreme Edition Ready for Sick Scores Mathematics Sandra Arithmetic Crypto Microsoft Excel Techgage March 10 2010 Retrieved February 9 2012 NVIDIA Tesla Personal Supercomputer Nvidia com Retrieved February 9 2012 AMD FireStream 9270 GPU Compute Accelerator Amd com Retrieved February 9 2012 K computer Achieves Goal of 10 Petaflops Fujitsu com Retrieved February 9 2012 See Japanese numbers Intel s Knights Corner 50 Core 22nm Co processor November 16 2011 Retrieved November 16 2011 Intel unveils 1 TFLOP s Knight s Corner Retrieved November 16 2011 Clark Don June 18 2012 IBM Computer Sets Speed Record The Wall Street Journal Retrieved June 18 2012 US Titan supercomputer clocked as world s fastest BBC November 12 2012 Retrieved February 28 2013 Oak Ridge Claims No 1 Position on Latest TOP500 List with Titan TOP500 Supercomputer Sites Top500 org November 12 2012 Retrieved February 28 2013 Montalbano Elizabeth October 11 2011 Oak Ridge Labs Builds Fastest Supercomputer Informationweek Retrieved February 9 2012 Tibken Shara October 29 2012 Titan supercomputer debuts for open scientific research Cutting Edge News CNet com Retrieved February 28 2013 Chinese Supercomputer Is Now The World s Fastest By A Lot Forbes Magazine June 17 2013 Retrieved June 17 2013 Feldman Michael China Races Ahead in TOP500 Supercomputer List Ending US Supremacy Top500 org Retrieved December 31 2016 June 2018 Top500 org Retrieved July 17 2018 Folding Home Active CPUs amp GPUs by OS foldingathome org Retrieved April 8 2020 Folding home March 25 2020 Thanks to our AMAZING community we ve crossed the exaFLOP barrier That s over a 1 000 000 000 000 000 000 operations per second making us 10x faster than the IBM Summit pic twitter com mPMnb4xdH3 foldingathome Retrieved April 4 2020 Folding Home Crushes Exascale Barrier Now Faster Than Dozens of Supercomputers ExtremeTech extremetech com Retrieved April 4 2020 Folding Home exceeds 1 5 ExaFLOPS in the battle against Covid 19 TechSpot Retrieved April 4 2020 Sony Computer Entertainment s Support for Folding home Project on PlayStation 3 Receives This Year s Good Design Gold Award Press release Sony Computer Entertainment Inc November 6 2008 Archived from the original on January 31 2009 Retrieved December 11 2008 BOINC Computing Power BOINC Retrieved December 28 2020 SETI Home Credit overview BOINC Retrieved June 15 2018 Einstein Home Credit overview BOINC Retrieved June 15 2018 MilkyWay Home Credit overview BOINC Retrieved June 15 2018 Internet PrimeNet Server Distributed Computing Technology for the Great Internet Mersenne Prime Search GIMPS Retrieved June 15 2018 1634 1699 McCusker J J 1997 How Much Is That in Real Money A Historical Price Index for Use as a Deflator of Money Values in the Economy of the United States Addenda et Corrigenda PDF American Antiquarian Society 1700 1799 McCusker J J 1992 How Much Is That in Real Money A Historical Price Index for Use as a Deflator of Money Values in the Economy of the United States PDF American Antiquarian Society 1800 present Federal Reserve Bank of Minneapolis Consumer Price Index estimate 1800 Retrieved April 16 2022 The IBM 7030 STRETCH Norman Hardy Retrieved February 24 2017 Loki and Hyglac Loki www lanl gov July 13 1997 Archived from the original on July 21 2011 Retrieved February 9 2012 Kentucky Linux Athlon Testbed 2 KLAT2 The Aggregate Retrieved February 9 2012 KASY0 The Aggregate August 22 2003 Retrieved February 9 2012 Microwulf A Personal Portable Beowulf Cluster Archived from the original on September 12 2007 Retrieved February 9 2012 Adam Stevenson Yann Le Du and Mariem El Afrit High performance computing on gamer PCs Ars Technica March 31 2011 Tom Logan January 9 2012 HD7970 Quadfire Eyefinity Review OC3D net Sony Sparks Price War With PS4 Priced at 399 CNBC June 11 2013 FreezePage Archived from the original on November 16 2013 Retrieved May 9 2020 FreezePage Archived from the original on December 19 2013 Retrieved May 9 2020 FreezePage Archived from the original on January 10 2015 Retrieved May 9 2020 Radeon R9 295X2 8 GB Review Project Hydra Gets Liquid Cooling April 8 2014 Perez Carol E July 13 2017 Building a 50 Teraflops AMD Vega Deep Learning Box for Under 3K Intuition Machine Retrieved July 26 2017 lowest fp16 mattebaughman s Saved Part List Celeron G3930 2 9GHz Dual Core Radeon RX VEGA 64 8GB 3 Way CrossFire XON 350 BK ATX Mid Tower pcpartpicker com Retrieved September 13 2017 System Builder pcpartpicker com Retrieved December 7 2020 AMD Playstation 5 GPU Specs techpowerup com Retrieved May 12 2021 Xbox Series X Xbox xbox com Retrieved September 21 2021 Nvidia Announces RTX 4090 Coming October 12 RTX 4080 Later tomshardware com September 20 2022 Retrieved September 20 2022 Retrieved from https en wikipedia org w index php title FLOPS amp oldid 1147079123, wikipedia, wiki, book, books, library,

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