FLOPS
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In computing, FLOPS (or flops or flop/s) is an acronym meaning FLoating point Operations Per Second. The FLOPS is a measure of a computer's performance, especially in fields of scientific calculations that make heavy use of floating point calculations, similar to instructions per second. Since the final S stands for "second", conservative speakers consider "FLOPS" as both the singular and plural of the term, although the singular "FLOP" is frequently encountered. Alternatively, the singular FLOP (or flop) is used as an abbreviation for "FLoating-point OPeration", and a flop count is a count of these operations (e.g., required by a given algorithm or computer program). In this context, "flops" is simply the plural rather than a rate. Computing devices exhibit an enormous range of performance levels in floating-point applications, so it makes sense to introduce larger units than FLOPS. The standard SI prefixes can be used for this purpose, resulting in such units as gigaFLOPS (one billion or 1×109 FLOPS), teraFLOPS (one trillion or 1×1012 FLOPS) and petaFLOPS (one quadrillion or 1×1015 FLOPS). IBM's top supercomputer, dubbed Blue Gene/P, is designed to continuously operate at speeds exceeding one petaFLOPS and, when configured to do so, should be able to reach speeds in excess of three petaFLOPS[1]. NEC's SX-9 supercomputer has a peak processing performance of 839 teraFLOPS and features the world's first vector processor to exceed 100 gigaFLOPS per single core. A basic calculator performs relatively few FLOPS. Each calculation request to a typical calculator requires only a single operation, so there is rarely any need for its response time to exceed that needed by the operator. Any response time below 0.1 second is perceived as instantaneous by a human operator, so a simple calculator needs only about 10 FLOPS.
Measuring performanceIn order for FLOPS to be useful as a measure of floating-point performance, a standard benchmark must be available on all computers of interest. One example is the LINPACK benchmark. There are many factors in computer performance other than raw floating-point computation speed, such as I/O performance, interprocessor communication, cache coherence, and the memory hierarchy. This means that supercomputers are in general only capable of a small fraction of their "theoretical peak" FLOPS throughput (obtained by adding together the theoretical peak FLOPS performance of every element of the system). Even when operating on large highly parallel problems, their performance will be bursty, mostly due to the residual effects of Amdahl's law. Real benchmarks therefore measure both peak actual FLOPS performance as well as sustained FLOPS performance. For ordinary (non-scientific) applications, integer operations (measured in MIPS) are far more common. Measuring floating point operation speed, therefore, does not predict accurately how the processor will perform on just any problem. However, for many scientific jobs such as analysis of data, a FLOPS rating is effective. Historically, the earliest reliably documented serious use of the Floating Point Operation as metric appears to be AEC justification to Congress for purchasing a Control Data CDC 6600 in the mid-1960s. The terminology is currently so confusing that until April 24, 2006 U.S. export control was based upon measurement of "Composite Theoretical Performance" (CTP) in millions of "Theoretical Operations Per Second" or MTOPS. On that date, however, the U.S. Department of Commerce's Bureau of Industry and Security amended the Export Administration Regulations to base controls on Adjusted Peak Performance (APP) in Weighted teraFLOPS (WT). RecordsOn February 4, 2008, The NSF and the University of Texas opened full scale research runs on an AMD, Sun supercomputer Ranger, the most powerful supercomputing system in the world for open science research, which operates at sustained speeds of half a petaflop. On October 25, 2007, NEC Corporation of Japan issued a press release announcing its SX series model SX-9, claiming it to be the world's fastest vector supercomputer with a peak processing performance of 839 teraFLOPS. The SX-9 features the first CPU capable of a peak vector performance of 102.4 gigaFLOPS per single core. 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. When configured to do so, it can reach speeds in excess of three petaFLOPS. 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 TFLOPS. The Cray XT4 hit second place with 101.7 TFLOPS. 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. Distributed computing uses the Internet to link personal computers to achieve a similar effect:
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