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copied!<p>The first thing I would do is concatenate your rotation and transform matricies into one matrix before you enter the for-loop ... that way you aren't calculating two matrix multiplications and a vector on every for-loop; instead you would only be multiplying a single vector and matrix. Secondly, you may want to look into unrolling your loop and then compiling with a higher optimization level (on <code>g++</code> I would use at least <code>-O2</code>, but I'm not familiar with MSVC, so you'll have to translate that optimization level yourself). That would avoid any overhead that branches in the code might incur, especially on cache-flushes. Lastly, if you haven't already looked into it, check into doing some SSE optimizations since you're dealing with vectors.</p> <p><strong>UPDATE</strong>: I'm going to add one last idea that would involve threading ... basically pipeline your vertices when you do your threading. So for instance, let's say you have a machine with eight available CPU threads (i.e., quad-core with hyper-threading). Setup six threads for the vertex pipeline processing, and use non-locking single-consumer/producer queues to pass messages between stages of the pipeline. Each stage will transform a single member of your six-member vertex-array. I'm guessing there are a bunch of these six-member vertex arrays, so setup in a stream that is passed through the pipeline, you can very efficiently process the stream, and avoid the use of mutexes and other locking semaphores, etc. For more info on a fast non-locking single-producer/consumer queue, <a href="https://stackoverflow.com/questions/6839425/what-will-be-the-critical-section-code-for-a-shared-queue-accessed-by-two-threads/6839544#6839544">see my answer here</a>. </p> <p><strong>UPDATE 2</strong>: You only have a dual-core processor ... so dump the pipeline idea since it's going to run into bottlenecks as each thread contends for CPU resources.</p>

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