Performance engineering within systems engineering encompasses the set of roles, skills, activities, practices, tools, and deliverables applied at every phase of the systems development life cycle which ensures that a solution will be designed, implemented, and operationally supported to meet the performance requirements defined for the solution.
It includes the roles, skills, activities, practices, tools and deliverables applied at every phase of the application lifecycle that ensure an application will be designed, implemented and operationally supported to meet non-functional performance requirements.
In computing, that service can be any unit of work from a simple disk IO to loading a complex web page.
Being relatively uninformed on computer benchmarks, some of them pick a particular CPU based on operating frequency (see megahertz myth).
Some system designers building parallel computers pick CPUs based on the speed per dollar.
[4][5] Information theory, developed by Claude E. Shannon during World War II, defines the notion of channel capacity and provides a mathematical model by which one can compute it.
In addition, the operating system can schedule when to perform the action that the process is commanding.
For example, suppose a process commands that a computer card's voltage output be set high-low-high-low and so on at a rate of 1000 Hz.
The operating system may choose to adjust the scheduling of each transition (high-low or low-high) based on an internal clock.
In computer networking, bandwidth is a measurement of bit-rate of available or consumed data communication resources, expressed in bits per second or multiples of it (bit/s, kbit/s, Mbit/s, Gbit/s, etc.).
For example, bandwidth tests measure the maximum throughput of a computer network.
In communication networks, throughput is essentially synonymous to digital bandwidth consumption.
Because the units of throughput are the reciprocal of the unit for propagation delay, which is 'seconds per message' or 'seconds per output', throughput can be used to relate a computational device performing a dedicated function such as an ASIC or embedded processor to a communications channel, simplifying system analysis.
System designers building parallel computers, such as Google's hardware, pick CPUs based on their speed per watt of power, because the cost of powering the CPU outweighs the cost of the CPU itself.
[8] Compression is useful because it helps reduce resource usage, such as data storage space or transmission capacity.
It can also serve to investigate, measure, validate, or verify other quality attributes of the system, such as scalability, reliability, and resource usage.
This is typically a computer application, but the same methods can be applied to economic markets, bureaucracies or other complex systems.
However, it satisfies some human needs: it appears faster to the user as well as provides a visual cue to let them know the system is handling their request.