Content deleted Content added
Add some discussion of basic block profiling, and add some current tools that support managed code to list of commonly used tools |
Describe some applications of performance profilers |
||
Line 30:
* An ongoing interaction with the [[hypervisor]] (continuous or periodic monitoring via on-screen display for instance)
: This provides the opportunity to switch a trace on or off at any desired point during execution in addition to viewing on-going metrics about the (still executing) program. It also provides the opportunity to suspend asynchronous processes at critical points to examine interactions with other parallel processes in more detail.
A profiler can be applied to an individual method or at the scale of a module or program, to identify performance bottlenecks by making long-running code obvious.<ref>{{cite web| title=How to find the performance bottleneck in C# desktop application?| publisher=[[Stack Overflow]]| year=2012| url=https://stackoverflow.com/questions/13698674/how-to-find-the-performance-bottleneck-in-c-sharp-desktop-application}}</ref> A profiler can be used to understand code from a timing point of view, with the objective of optimizing it to handle various runtime conditions<ref>{{cite web| last=Krauss| first=Kirk J| title=Performance Profiling with a Focus| publisher=Develop for Performance| year=2017| url=http://www.developforperformance.com/PerformanceProfilingWithAFocus.html}}</ref> or various loads<ref>{{cite web| work=Stackify Developer Tips, Tricks and Resources| title=What is code profiling? Learn the 3 Types of Code Profilers| publisher=Disqus| year=2016| url=https://stackify.com/what-is-code-profiling/}}</ref>. Profiling results can be ingested by a compiler that provides [[profile-guided optimization]].<ref>{{cite web| last=Lawrence| first=Eric| work=testslashplain| title=Getting Started with Profile Guided Optimization| publisher=WordPress| year=2016| url=https://textslashplain.com/2016/01/10/getting-started-with-profile-guided-optimization/}}</ref> Profiling results can be used to guide the design and optimization of an individual algorithm; the [[Krauss matching wildcards algorithm]] is an example.<ref>{{cite web| last=Krauss| first=Kirk| title=Matching Wildcards: An Improved Algorithm for Big Data| publisher=Develop for Performance| year=2018| url=http://www.developforperformance.com/MatchingWildcards_AnImprovedAlgorithmForBigData.html}}</ref> Profilers are built into some [[application performance management]] systems that aggregate profiling data to provide insight into [[transaction processing|transaction]] workloads in [[distributed computing|distributed]] applications.<ref>{{cite web| work=Stackify Developer Tips, Tricks and Resources| title=List of .Net Profilers: 3 Different Types and Why You Need All of Them| publisher=Disqus| year=2016| url=https://stackify.com/three-types-of-net-profilers/}}</ref>
==History==
| |||