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The answer is 42! Saturday, September 28, 2013. Summer of 2013 with Numpy and Google. GSoC is a learning process - we learn to work together to solve a big problem by breaking it down into smaller chunks. This year, 2013. I got chance to work as student contributor at Numpy. And the experience was worth paying the amount of effort. I have joined Numpy, the community thats quite friendly and helpful. I have written the summary of project into two post : Profiling. What I gained this year? The most challen...

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The answer is 42! Saturday, September 28, 2013. Summer of 2013 with Numpy and Google. GSoC is a learning process - we learn to work together to solve a big problem by breaking it down into smaller chunks. This year, 2013. I got chance to work as student contributor at Numpy. And the experience was worth paying the amount of effort. I have joined Numpy, the community thats quite friendly and helpful. I have written the summary of project into two post : Profiling. What I gained this year? The most challen...

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Arink`s Blog | arinkverma.in Reviews

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The answer is 42! Saturday, September 28, 2013. Summer of 2013 with Numpy and Google. GSoC is a learning process - we learn to work together to solve a big problem by breaking it down into smaller chunks. This year, 2013. I got chance to work as student contributor at Numpy. And the experience was worth paying the amount of effort. I have joined Numpy, the community thats quite friendly and helpful. I have written the summary of project into two post : Profiling. What I gained this year? The most challen...

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Arink`s Blog: Speedup UFUNC_CHECK_STATUS by avoiding heavy clearing flag

http://www.arinkverma.in/2013/09/speedup-ufunccheckstatus-by-avoiding.html

The answer is 42! Saturday, September 14, 2013. Speedup UFUNC CHECK STATUS by avoiding heavy clearing flag. Is just single macro which do both checking clearing the error flags. It clear error flags every time after checking. We should avoid clear operation if not needed, as it is a bit expensive and take significant amount of time. Before each ufunc loop when. Combined was around 10%. Which is now dropped to 1%. For operation which don't raise any error. X = np.asarray([1]); x x;. Google Summer of Code.

2

Arink`s Blog: GSoC'13 Project Summary-1 : Numpy's profiling

http://www.arinkverma.in/2013/09/gsoc13-project-summary-1-numpys.html

The answer is 42! Monday, September 23, 2013. GSoC'13 Project Summary-1 : Numpy's profiling. Small numpy arrays are very similar to Python scalars but numpy incurs a fair amount of extra overhead for simple operations. For large arrays this doesn't matter, but for code that manipulates a lot of small pieces of data, it can be a serious bottleneck. Profiling simple operations like the above. Make sure to build it from source. Clone svn repository from http:/ gperftools.googlecode.com/svn/trunk/. First, ru...

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Arink`s Blog: GSoC'13 Project Summary-2 : Numpy's Bottlenecks and its Removal

http://www.arinkverma.in/2013/09/gsoc13-project-summary-2-numpys.html

The answer is 42! Wednesday, September 25, 2013. GSoC'13 Project Summary-2 : Numpy's Bottlenecks and its Removal. I have mentioned the tools which I used for profiling numpy. Call-graph, made my life not easier but a bit simpler to detect time consuming methods. But time taken just indicate the possibility of bottlenecks as many of time consuming methods are highly optimized. Hence, critically reading code along with call-graph is the trick. Following types bottlenecks were observed. Together use signifi...

4

Arink`s Blog: Improvement in _extract_pyvals

http://www.arinkverma.in/2013/09/improvement-in-extractpyvals.html

The answer is 42! Wednesday, September 11, 2013. Improvement in extract pyvals. Errobj = Py BuildValue("NO", PyBytes FromString(name), retval);. It alone takes 10% of time, with every operations. Its better to avoid packing of string instead assign pointer to struct and stash them to thread local storage. Hence no allocations would be need to for errorobj. Every-time, which almost goes unused. Error object include name of ufunc and callback pointer. X = np.asarray([5.0,1.0]); x x. View my complete profile.

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Arink`s Blog: Scope for improvement in _extract_pyvals

http://www.arinkverma.in/2013/09/scope-for-improvement-in-extractpyvals.html

The answer is 42! Monday, September 9, 2013. Scope for improvement in extract pyvals. I my last post, I mentioned how two functions,. Together use 12% of time. But major culprit is. Errobj = Py BuildValue("NO", PyBytes FromString(name), retval);. It alone takes 10% of time, with every operations. First approach I take, was to cached Py BuildValue with Thread storage or dict. With this time consumption of extract pyvals dropped to 4%. Errorobj caching with PyThreadState GetDict. Has been made at pr #3686.

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Arink`s Blog

The answer is 42! Saturday, September 28, 2013. Summer of 2013 with Numpy and Google. GSoC is a learning process - we learn to work together to solve a big problem by breaking it down into smaller chunks. This year, 2013. I got chance to work as student contributor at Numpy. And the experience was worth paying the amount of effort. I have joined Numpy, the community thats quite friendly and helpful. I have written the summary of project into two post : Profiling. What I gained this year? The most challen...

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