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    <p>Simply put, most definetly. Read on for some discussion.</p> <p>Tuning a service is an art-form or requires benchmarking (and the space for the amount of concepts you need to benchmark is huge). I believe that it depends on factors such as the following (this is not exhaustive).</p> <ol> <li>how much time an item which is picked up from the ready qeueue takes to process, and</li> <li>how many worker threads are their? </li> <li>how many producers are their, and how often do they produce ? </li> <li>what type of wait concepts are you using ? spin-locks or kernel-waits (the latter being slower) ? </li> </ol> <p>So, if items are produced often, and if the amount of threads is large, and the processing time is low: the data structure <strong>could</strong> be locked for large windows, thus causing thrashing.</p> <p>Other factors may include the data structure used and how long the data structure is locked for -e.g., if you use a linked list to manage such a queue the <code>add</code> and <code>remove</code> oprations take constant time. A prio-queue (heaps) takes a few more operations on average when items are <code>added</code>.</p> <p>If your system is for business processing you could take this question out of the picture by just using:</p> <ol> <li>A process based architecure and just spawning multiple producer consumer processes and using the file system for communication,</li> <li>Using a non-preemtive collaborative threading programming language such as stackless python, Lua or Erlang.</li> </ol> <p>also note: synchronization primitives cause inter-processor cache-cohesion floods which are <a href="http://portal.acm.org/citation.cfm?id=1089104" rel="nofollow noreferrer">not good</a> and therefore should be used sparingly.</p> <p>The discussion could go on to fill a Ph.D dissertation :D</p>
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