Thomas Retornaz

Results 10 issues of Thomas Retornaz

**First pull request around isue #107** - Add all_of,any_of,copy,copy_n,count,count_if,equal,fill,find,find_if,find_if_not,lexicographical_compare,max,max_element,min,min_element,none_of,reduce,replace,replace_if,transform,transform_reduce "STL" like algorithm - Provide non regressions tests (Validated on Visual2017 and GCC) and documentation - Please pay attention on workaround...

Hi When i made benchmark on std::like algorithm (see #107 and #115) i felt onto surprising behavior std::transform algorithm is faster than simd counterpart WTF i said on my desk...

bug

Hi I heavily use google benchmark (https://github.com/google/benchmark) on various projects. Linked to isssue #107, it may a good thing to have a benchmark to measure the provided speedup on various...

enhancement

Hi I currently migrate from boost:simd to libsimdpp I heavily use transform and reduce algorithm from plain pointers and simd aware operators I will try to implement such algorithm using...

enhancement

Hi i migrate from boost::simd to nsimd It seems that nsimd doesnt provide high level STL like algorithm (Transform,Reduce,etc...) I could try to implement them on my side Questions: Where...

enhancement

…ransform tests and benchmarks Note: Maxtree approach seems exists for under/overbuild but i don't find a paper which presents the algorithm So may the provide algorithms are not the fastest...

see From connected operators to levelings' [Meyer,1998] In ISMM '98: Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processingJune 1998 Pages 191–198...

…tzones variation around labeling using a "naïve" algorithm for discuss Todo find a way to merge fast label_components with flat and lambda flat

First of all, thanks for this awesome library ## 🚀 Feature Add support of List(List(Tensors)) in onnx export facilities ## Motivation (Note i already ask on pytorch forum but without...

module: onnx
feature
triaged