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Floating point operations per second (FLOPS, flops or flop/s) is a measure of computer performance in computing, useful in fields of scientific computations that require floating-point calculations. [1] For such cases, it is a more accurate measure than measuring instructions per second. [citation needed]
This allowed the system to work on different problems when the data was too small to demand the entire 256-PE array. [19] Based on a 25 MHz clock, with all 256-PEs running on a single program, the machine was designed to deliver 1 billion floating point operations per second, or in today's terminology, 1 GFLOPS. [20]
In 1978, the program was updated to log running time of each of the tests, allowing MFLOPS (Millions of Floating Point Operations Per Second) to be included in reports, along with an estimation of Integer MIPS (Millions of Instructions Per Second). In 1987, MFLOPS calculations were included in the log for the three appropriate tests and MOPS ...
Zettascale computing refers to computing systems capable of calculating at least "10 21 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (zetta FLOPS)". [1] It is a measure of supercomputer performance, and as of July 2022 [update] is a hypothetical performance barrier. [ 2 ]
The Dhrystone benchmark contains no floating point operations, thus the name is a pun on the then-popular Whetstone benchmark for floating point operations. The output from the benchmark is the number of Dhrystones per second (the number of iterations of the main code loop per second).
Instructions per second (IPS) is a measure of a computer's processor speed. For complex instruction set computers (CISCs), different instructions take different amounts of time, so the value measured depends on the instruction mix; even for comparing processors in the same family the IPS measurement can be problematic.
With more random divisors the average time per FDIV was approximately 50 clock cycles, i.e. 10 cycles added to check the divisor: Only 5 out of 1024 random divisors would trigger the scaling fixup. Since FDIV is a rare operation in most programs, the normal slowdown with the fix installed was typically a percent or less. [8]
Petascale computing refers to computing systems capable of performing at least 1 quadrillion (10^15) floating-point operations per second (FLOPS).These systems are often called petaflops systems and represent a significant leap from traditional supercomputers in terms of raw performance, enabling them to handle vast datasets and complex computations.