Analysis of parallel algorithms

<p>In <a href="/facts/Computer_science/lN3pEyPz">computer science</a>, analysis of parallel algorithms is the process of finding the <a href="/facts/Computational_complexity/Qenh22Ja">computational complexity</a> of <a href="/facts/Algorithm/fnl5NmRt">algorithms</a> executed in <a href="/facts/Parallel_computing/nQzcpzQt">parallel</a> – the amount of time, storage, or other <a href="/facts/System_resource/bX958SEx">resources</a> needed to execute them. In many respects, analysis of <a href="/facts/Parallel_algorithm/nUPzEF4C">parallel algorithms</a> is similar to <a href="/facts/Analysis_of_algorithms/pStoBgBn">the analysis</a> of <a href="/facts/Sequential_algorithm/Jl5SxP1U">sequential algorithms</a>, but is generally more involved because one must reason about the behavior of multiple cooperating <a href="/facts/Thread_(computing)/hh8WHyPd">threads</a> of execution. One of the primary goals of parallel analysis is to understand how a parallel algorithm's use of resources (speed, space, etc.) changes as the number of processors is changed.
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Analysis of parallel algorithms open-in-new

Analysis of parallel algorithms