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POPerformance: vector of classes or a class containing vectors
 

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  1. POPerformance: vector of classes or a class containing vectors
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    <p>I have a class containing a number of double values. This is stored in a vector where the indices for the classes are important (they are referenced from elsewhere). The class looks something like this:</p> <h2>Vector of classes</h2> <pre><code>class A { double count; double val; double sumA; double sumB; vector&lt;double&gt; sumVectorC; vector&lt;double&gt; sumVectorD; } vector&lt;A&gt; classes(10000); </code></pre> <p>The code that needs to run as fast as possible is something like this:</p> <pre><code>vector&lt;double&gt; result(classes.size()); for(int i = 0; i &lt; classes.size(); i++) { result[i] += classes[i].sumA; vector&lt;double&gt;::iterator it = find(classes[i].sumVectorC.begin(), classes[i].sumVectorC.end(), testval); if(it != classes[i].sumVectorC.end()) result[i] += *it; } </code></pre> <p>The alternative is instead of one giant loop, split the computation into two separate loops such as:</p> <pre><code>for(int i = 0; i &lt; classes.size(); i++) { result[i] += classes[i].sumA; } for(int i = 0; i &lt; classes.size(); i++) { vector&lt;double&gt;::iterator it = find(classes[i].sumVectorC.begin(), classes[i].sumVectorC.end(), testval); if(it != classes[i].sumVectorC.end()) result[i] += *it; } </code></pre> <p>or to store each member of the class in a vector like so:</p> <h2>Class of vectors</h2> <pre><code>vector&lt;double&gt; classCounts; vector&lt;double&gt; classVal; ... vector&lt;vector&lt;double&gt; &gt; classSumVectorC; ... </code></pre> <p>and then operate as:</p> <pre><code>for(int i = 0; i &lt; classes.size(); i++) { result[i] += classCounts[i]; ... } </code></pre> <p>Which way would usually be faster (across x86/x64 platforms and compilers)? Are look-ahead and cache lines are the most important things to think about here?</p> <h2>Update</h2> <p>The reason I'm doing a linear search (i.e. find) here and not a hash map or binary search is because the sumVectors are very short, around 4 or 5 elements. Profiling showed a hash map was slower and a binary search was slightly slower.</p>
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    1. COis this homework?
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    2. CONo definitely not, I'm optimising an inner loop in a clustering algorithm and am wondering about the tradeoff between these two approaches.
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    3. CO@Khaki The implementation seems easy enough to build both and do good old measuring :-)
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