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Computing
Data Structure for Matrix Implementation
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<blockquote data-quote="Stefan Zota" data-source="post: 26028" data-attributes="member: 963"><p>Vectors of vectors provides very slow access time. It has also storage limitations.</p><p> </p><p>Fastest solution is to use a simple array. This provides quick access (continous memory), optimal storage (no fragmentation).</p><p>The downside is that you need to do some work to write all functions needed for a matrix. This gets trickier when you are looking at banded/sparse matrices. In the end, I can tell you from my own experience it is worth it. You can process 10k * 10k matrices on a personal computer.</p><p> </p><p>Alain's solution is good too, it depends if you want to practice C++ or you focus on numerical portion.</p></blockquote><p></p>
[QUOTE="Stefan Zota, post: 26028, member: 963"] Vectors of vectors provides very slow access time. It has also storage limitations. Fastest solution is to use a simple array. This provides quick access (continous memory), optimal storage (no fragmentation). The downside is that you need to do some work to write all functions needed for a matrix. This gets trickier when you are looking at banded/sparse matrices. In the end, I can tell you from my own experience it is worth it. You can process 10k * 10k matrices on a personal computer. Alain's solution is good too, it depends if you want to practice C++ or you focus on numerical portion. [/QUOTE]
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