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Hub AI
Performance tuning AI simulator
(@Performance tuning_simulator)
Hub AI
Performance tuning AI simulator
(@Performance tuning_simulator)
Performance tuning
Performance tuning is the improvement of system performance. Typically in computer systems, the motivation for such activity is called a performance problem, which can be either real or anticipated. Most systems will respond to increased load with some degree of decreasing performance. A system's ability to accept higher load is called scalability, and modifying a system to handle a higher load is synonymous to performance tuning.
Systematic tuning follows these steps:
This is an instance of the measure-evaluate-improve-learn cycle from quality assurance.
A performance problem may be identified by slow or unresponsive systems. This usually occurs because high system loading, causing some part of the system to reach a limit in its ability to respond. This limit within the system is referred to as a bottleneck.
A handful of techniques are used to improve performance. Among them are code optimization, load balancing, caching strategy, distributed computing and self-tuning.
Performance analysis, commonly known as profiling, is the investigation of a program's behavior using information gathered as the program executes. Its goal is to determine which sections of a program to optimize.
A profiler is a performance analysis tool that measures the behavior of a program as it executes, particularly the frequency and duration of function calls. Performance analysis tools existed at least from the early 1970s. Profilers may be classified according to their output types, or their methods for data gathering.
Performance engineering is the discipline encompassing roles, skills, activities, practices, tools, and deliverables used to meet the non-functional requirements of a designed system, such as increase business revenue, reduction of system failure, delayed projects, and avoidance of unnecessary usage of resources or work.
Performance tuning
Performance tuning is the improvement of system performance. Typically in computer systems, the motivation for such activity is called a performance problem, which can be either real or anticipated. Most systems will respond to increased load with some degree of decreasing performance. A system's ability to accept higher load is called scalability, and modifying a system to handle a higher load is synonymous to performance tuning.
Systematic tuning follows these steps:
This is an instance of the measure-evaluate-improve-learn cycle from quality assurance.
A performance problem may be identified by slow or unresponsive systems. This usually occurs because high system loading, causing some part of the system to reach a limit in its ability to respond. This limit within the system is referred to as a bottleneck.
A handful of techniques are used to improve performance. Among them are code optimization, load balancing, caching strategy, distributed computing and self-tuning.
Performance analysis, commonly known as profiling, is the investigation of a program's behavior using information gathered as the program executes. Its goal is to determine which sections of a program to optimize.
A profiler is a performance analysis tool that measures the behavior of a program as it executes, particularly the frequency and duration of function calls. Performance analysis tools existed at least from the early 1970s. Profilers may be classified according to their output types, or their methods for data gathering.
Performance engineering is the discipline encompassing roles, skills, activities, practices, tools, and deliverables used to meet the non-functional requirements of a designed system, such as increase business revenue, reduction of system failure, delayed projects, and avoidance of unnecessary usage of resources or work.
