Information about Performance Tuning
Performance tuning is the improvement of system performance. This is typically a computer application, but the same methods can be applied to economic markets, bureaucracies or other complex systems. The motivation for such activity is called a performance problem, which can be 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, and distributed computing, and self-tuning.
Enhancing performance by rewriting specific portions of a program to run faster is one form of code optimization. The term code optimization can refer to improving the implementation of a particular algorithm for performing a task (code tuning). It can also refer to utilizing a better algorithm. Examples of code optimization include improving the code so that work is done once before a loop rather than inside a loop or replacing a call to a simple selection sort with a call to the more complicated algorithm for a quicksort.
Caching is a fundamental method of removing performance bottlenecks that are the result of slow access to data. Caching improves performance by retaining frequently used information in high speed memory, which reduces access time and thus improves performance. Caching is an effective manner of improving performance in situations where the principle of locality of reference applies.
The methods used to determine which data is stored in progressively faster storage are collectively called caching strategies.
A system can consist of independent components, each able to service requests. If all the requests are serviced by one of these systems (or a small number) while others remain idle then time is wasted waiting for used system to be available. Arranging so all systems are used equally is referred to as load balancing and can improve over-all performance.
Load balancing is often used to achieve further gains from a distributed system by intelligently selecting which machine to run an operation on based on how busy all potential candidates are, and how well suited each machine is to the type of operation that needs to be performed.
Distributed computing is used to increase the performance of operations that can be performed in parallel, by concurrently executing multiple operations. Operations may be distributed across multiple processes on a single CPU, taking advantage of multitasking, multiple processes across multiple CPUs, or across multiple machines. As operations are executed concurrently, ensuring synchronization between processes is essential to ensure correct results.
As the trend of increasing the potential for parallel execution on modern CPU architectures continues, the use of distributed systems is essential to achieve performance benefits from the available parallelism. High performance cluster computing is a well known use of distributed systems for performance improvements.
Distributed computing and clustering can negatively impact latency while simultaneously increasing load on shared resources, such as database systems. To minimize latency and avoid bottlenecks, distributed computing can benefit significantly from distributed caches.
A self-tuning system is capable of optimizing its own internal running parameters in order to maximize or minimize the fulfillment of an objective function; typically efficiency or error. Self-tuning systems typically exhibit non-linear adaptive control. Self-tuning systems have been a hallmark of the aerospace industry for decades, as this sort of feedback is necessary to generate optimal multi-variable control for nonlinear processes.
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Systematic tuning follows these steps:
- Assess the problem and establish numeric values that categorize acceptable behavior.
- Measure the performance of the system before modification.
- Identify the part of the system that is critical for improving the performance. This is called the bottleneck.
- Modify that part of the system to remove the bottleneck.
- Measure the performance of the system after modification.
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, and distributed computing, and self-tuning.
Performance analysis
- See the main article at Performance analysis
Performance engineering
- See the main article at Performance engineering
Code optimization
- See the main article at Optimization (computer science).
Enhancing performance by rewriting specific portions of a program to run faster is one form of code optimization. The term code optimization can refer to improving the implementation of a particular algorithm for performing a task (code tuning). It can also refer to utilizing a better algorithm. Examples of code optimization include improving the code so that work is done once before a loop rather than inside a loop or replacing a call to a simple selection sort with a call to the more complicated algorithm for a quicksort.
Caching strategy
Caching is a fundamental method of removing performance bottlenecks that are the result of slow access to data. Caching improves performance by retaining frequently used information in high speed memory, which reduces access time and thus improves performance. Caching is an effective manner of improving performance in situations where the principle of locality of reference applies.
The methods used to determine which data is stored in progressively faster storage are collectively called caching strategies.
Load balancing
A system can consist of independent components, each able to service requests. If all the requests are serviced by one of these systems (or a small number) while others remain idle then time is wasted waiting for used system to be available. Arranging so all systems are used equally is referred to as load balancing and can improve over-all performance.
Load balancing is often used to achieve further gains from a distributed system by intelligently selecting which machine to run an operation on based on how busy all potential candidates are, and how well suited each machine is to the type of operation that needs to be performed.
Distributed computing
Distributed computing is used to increase the performance of operations that can be performed in parallel, by concurrently executing multiple operations. Operations may be distributed across multiple processes on a single CPU, taking advantage of multitasking, multiple processes across multiple CPUs, or across multiple machines. As operations are executed concurrently, ensuring synchronization between processes is essential to ensure correct results.
As the trend of increasing the potential for parallel execution on modern CPU architectures continues, the use of distributed systems is essential to achieve performance benefits from the available parallelism. High performance cluster computing is a well known use of distributed systems for performance improvements.
Distributed computing and clustering can negatively impact latency while simultaneously increasing load on shared resources, such as database systems. To minimize latency and avoid bottlenecks, distributed computing can benefit significantly from distributed caches.
Self-tuning
A self-tuning system is capable of optimizing its own internal running parameters in order to maximize or minimize the fulfillment of an objective function; typically efficiency or error. Self-tuning systems typically exhibit non-linear adaptive control. Self-tuning systems have been a hallmark of the aerospace industry for decades, as this sort of feedback is necessary to generate optimal multi-variable control for nonlinear processes.
Performance tools
- JINSPIRED JXInsight
- Performance Application Programming Interface
- OPNET Technologies
- NetSim
- Online CPU and GPU Optimization for video game technology
System (from Latin systēma, in turn from Greek σύστημα systēma) is a set of entities, real or abstract, where each entity interacts with, or is related to, at least one other
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performance, in performing arts, generally comprises an event in which one group of people (the performer or performers) behave in a particular way for another group of people (the audience).
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In UNIX computing, the system load is a measure of the amount of work that a computer system is doing. The load average is the average system load over a period of time.
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In telecommunications and software engineering, scalability is a desirable property of a system, a network, or a process, which indicates its ability to either handle growing amounts of work in a graceful manner, or to be readily enlarged.
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Bottleneck may refer to:
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- Bottleneck (engineering)
- Bottleneck (logistics)
- Bottleneck (traffic)
- Bottleneck guitar, also known as slide guitar
- Free State Bottleneck, a quasi-state that existed in Germany during the time of the Weimar Republic
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Load may refer to:
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- Structural load, forces which are applied to a structure
- Cargo, Freight, or Lading
- The load of a mutual fund (see Mutual fund fees and expenses)
- The genetic load of a population
- The parasite load of an organism
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Bottleneck may refer to:
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- Bottleneck (engineering)
- Bottleneck (logistics)
- Bottleneck (traffic)
- Bottleneck guitar, also known as slide guitar
- Free State Bottleneck, a quasi-state that existed in Germany during the time of the Weimar Republic
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In software engineering, performance analysis, more commonly profiling, is the investigation of a program's behavior using information gathered as the program runs (i.e. it is a form of dynamic program analysis, as opposed to static code analysis).
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Within Systems engineering, Performance engineering encompasses the set of roles, skills, activities, practices, tools, and deliverables applied at every phase of the Systems Development Lifecycle which ensures that a solution will be designed, implemented, and operationally
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In computing, optimization is the process of modifying a system to make some aspect of it work more efficiently or use fewer resources. For instance, a computer program may be optimized so that it executes more rapidly, or is capable of operating within a reduced amount of memory
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In mathematics, computing, linguistics, and related disciplines, an algorithm is a finite list of well-defined instructions for accomplishing some task that, given an initial state, will proceed through a well-defined series of successive states, eventually terminating in an
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Selection sort is a sorting algorithm, specifically an in-place comparison sort. It has Θ(n2) complexity, making it inefficient on large lists, and generally performs worse than the similar insertion sort.
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Quicksort is a well-known sorting algorithm developed by C. A. R. Hoare that, on average, makes (big O notation) comparisons to sort n items. However, in the worst case, it makes comparisons.
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cache (IPA:/kæʃ/, like "catch" [1]) is a collection of data duplicating original values stored elsewhere or computed earlier, where the original data is expensive to fetch (due to longer access time) or to
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In computer science, locality of reference, also called the principle of locality, is the term applied to situations where the same value or related storage locations are frequently accessed.
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In computer networking, load balancing is a technique (usually performed by load balancers) to spread work between many computers, processes, hard disks or other resources in order to get optimal resource utilization and decrease computing time.
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In computer networking, load balancing is a technique (usually performed by load balancers) to spread work between many computers, processes, hard disks or other resources in order to get optimal resource utilization and decrease computing time.
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Distributed computing is a method of computer processing in which different parts of a program run simultaneously on two or more computers that are communicating with each other over a network.
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Distributed computing is a method of computer processing in which different parts of a program run simultaneously on two or more computers that are communicating with each other over a network.
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central processing unit (CPU), or sometimes simply processor, is the component in a digital computer capable of executing a program.(Knott 1974) It interprets computer program instructions and processes data.
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In computing, multitasking is a method by which multiple tasks, also known as processes, share common processing resources such as a CPU. In the case of a computer with a single CPU, only one task is said to be running
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Parallel computing is the simultaneous execution of some combination of multiple instances of programmed instructions and data on multiple processors in order to obtain results faster.
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A computer cluster is a group of tightly coupled computers that work together closely so that in many respects they can be viewed as though they are a single computer. The components of a cluster are commonly, but not always, connected to each other through fast local area
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cache (IPA:/kæʃ/, like "catch" [1]) is a collection of data duplicating original values stored elsewhere or computed earlier, where the original data is expensive to fetch (due to longer access time) or to
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A self-tuning system is capable of optimizing its own internal running parameters in order to maximize or minimize the fulfillment of an objective function; typically efficiency or error. Self-tuning systems typically exhibit non-linear adaptive control.
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In mathematics, the term optimization, or mathematical programming, refers to the study of problems in which one seeks to minimize or maximize a real function by systematically choosing the values of real or integer variables from within an allowed set.
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Efficiency as a technical term may refer to:
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- Energy efficiency, useful work per quantity of energy
- Energy conversion efficiency, desired energy output per energy input
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Error refers to a difference between actual behavior or measurement and the norms or expectations for the behavior or measurement. The concrete meaning of the Latin word error
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nonlinear system is a system which is not linear i.e. a system which does not satisfy the superposition principle. Less technically, a nonlinear system is any problem where the variable(s) to be solved for cannot be written as a linear sum of independent components.
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