#I7 6700k gflops fp64 64 Bit#
įLOPS 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. 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.įLOPS on an HPC-system can be calculated using this equation: FLOPS = racks × nodes rack × sockets node × cores socket × cycles second × FLOPs cycle. 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. 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. Examples of integer operation include data movement (A to B) or value testing (If A = B, then C).
The unit MIPS measures integer performance of a computer. Floating-point operations are typically used in fields such as scientific computational research. Computational performance įLOPS and MIPS are units of measure for the numerical computing performance of a computer. As such, floating-point processors are ideally suited for computationally intensive applications. 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. 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. 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). While several similar formats are in use, the most common is ANSI/IEEE Std. 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). Floating-point representation is similar to scientific notation, except everything is carried out in base two, rather than base ten.
For such cases, it is a more accurate measure than measuring instructions per second.įloating-point arithmetic is needed for very large or very small real numbers, or computations that require a large dynamic range. 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. FLOPS by the largest supercomputer over time
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