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CPU time (or process time) is the amount of time that a central processing unit (CPU) was used for processing instructions of a computer program or operating system. CPU time is measured in clock ticks or seconds. Sometimes it is useful to convert CPU time into a percentage of the CPU capacity, giving the CPU usage.
Conversely, some people try to increase performance of a CPU by replacing the oscillator crystal with a higher frequency crystal ("overclocking"). [4] However, the amount of overclocking is limited by the time for the CPU to settle after each pulse, and by the extra heat created.
Because the GPU has fast and local hardware access to every pixel or other picture element in an image, it can analyze and average it (for the first example) or apply a Sobel edge filter or other convolution filter (for the second) with much greater speed than a CPU, which typically must access slower random-access memory copies of the graphic ...
The purpose of overclocking is to increase the operating speed of a given component. [3] Normally, on modern systems, the target of overclocking is increasing the performance of a major chip or subsystem, such as the main processor or graphics controller, but other components, such as system memory or system buses (generally on the motherboard), are commonly involved.
In certain applications requiring massive vector operations, this can yield several orders of magnitude higher performance than a conventional CPU. The two largest discrete (see " Dedicated graphics processing unit " above) GPU designers, AMD and Nvidia , are pursuing this approach with an array of applications.
This level of performance is primarily enabled by the cumulative effort of a vast array of powerful GPU and CPU units. [71] As of December 2020, the entire BOINC network averages about 31 petaFLOPS. [72] As of June 2018, SETI@home, employing the BOINC software platform, averages 896 teraFLOPS. [73]
In 2006, Nvidia's GPU had a 4x performance advantage over other CPUs. In 2018 the Nvidia GPU was 20 times faster than a comparable CPU node: the GPUs were 1.7x faster each year. Moore's law would predict a doubling every two years, however Nvidia's GPU performance was more than tripled every two years, fulfilling Huang's law. [5]
The useful work that can be done with any computer depends on many factors besides the processor speed. These factors include the instruction set architecture, the processor's microarchitecture, and the computer system organization (such as the design of the disk storage system and the capabilities and performance of other attached devices), the efficiency of the operating system, and the high ...