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Linear Constraints | Notes on Computer Graphics Programming and Applied Mathematics

Notes on Computer Graphics Programming and Applied Mathematics. September 21, 2014. September 21, 2014. Last week I was in charge of optimizing our NEON code. Most part of this work is to do shuffling/swizzling using NEON’s vdup, vext, etc. This is not a hard work but I think this could be automated. The general idea is to model it as a 2-sources shortest path problem. We can construct the graph as follow:. A path in the graph is a sequence application of target instructions. It is called “undefine...

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Linear Constraints | Notes on Computer Graphics Programming and Applied Mathematics | linearconstraints.net Reviews
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Notes on Computer Graphics Programming and Applied Mathematics. September 21, 2014. September 21, 2014. Last week I was in charge of optimizing our NEON code. Most part of this work is to do shuffling/swizzling using NEON’s vdup, vext, etc. This is not a hard work but I think this could be automated. The general idea is to model it as a 2-sources shortest path problem. We can construct the graph as follow:. A path in the graph is a sequence application of target instructions. It is called “undefine...
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Linear Constraints | Notes on Computer Graphics Programming and Applied Mathematics | linearconstraints.net Reviews

https://linearconstraints.net

Notes on Computer Graphics Programming and Applied Mathematics. September 21, 2014. September 21, 2014. Last week I was in charge of optimizing our NEON code. Most part of this work is to do shuffling/swizzling using NEON’s vdup, vext, etc. This is not a hard work but I think this could be automated. The general idea is to model it as a 2-sources shortest path problem. We can construct the graph as follow:. A path in the graph is a sequence application of target instructions. It is called “undefine...

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Linear Constraints | Notes on Computer Graphics Programming and Applied Mathematics

Notes on Computer Graphics Programming and Applied Mathematics. September 21, 2014. September 21, 2014. Last week I was in charge of optimizing our NEON code. Most part of this work is to do shuffling/swizzling using NEON’s vdup, vext, etc. This is not a hard work but I think this could be automated. The general idea is to model it as a 2-sources shortest path problem. We can construct the graph as follow:. A path in the graph is a sequence application of target instructions. It is called “undefine...

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