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Fix and optimize handling of vectorized memory accesses (apache#17767)
* Vectorized loads for binary elemwise kernel * More generalization * Add backwardusenone * Remove the unused _backward_add op * Add vectorized backwardusein * Extending vectorization to more binary ops, binary ops with scalar and unary ops * Handling ElementwiseSum * Get rid of half2 in mshadow * Remove backward_elemwiseaddex * Revert "Remove the unused _backward_add op" This reverts commit f86da86. * Revert "Remove backward_elemwiseaddex" This reverts commit 7729114. * Add back the backward_add since C++ test relies on it * Test bcast implementations * First version of vecotrized bcast * Adding single side vectorized bcast kernel * Removing debug prints * Actually run the single side kernel * Move the default implementation of bcast to the vectorized one * Limit the new implementation to GPU only * Enabling vectorization when broadcast does not actually do broadcast * Cleaning * Cleaning part 2 * Fix for numpy ops using stuff from broadcast * Fix * Fix lint * Try to debug pinv numpy test * Fix * Fix the vectorized broadcast implementation for misaligned input pointers * Added tests * Added docs to cuda_vectorization.cuh * Another fix for broadcast and fix INT64 compilation * Optimize for aligned=true * 1 more addition to test * Reverting the change to Numpy op test * Trying mcmodel=medium to fix the failure in CMake static build * Revert "Trying mcmodel=medium to fix the failure in CMake static build" This reverts commit 1af684c. * Limiting the PR to just elementwise ops
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