[GitHub] [incubator-mxnet] xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU.

xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU. URL: https://github.com/apache/incubator-mxnet/issues/15928#issuecomment-528001954 @ptrendx @yzhliu I will create a PR for `np.random.gamma` implemented using the method I proposed before the end of

[GitHub] [incubator-mxnet] xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU.

xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU. URL: https://github.com/apache/incubator-mxnet/issues/15928#issuecomment-522469258 @ptrendx The device-side api I mentioned is the `RandGenerator` class. (the one used in `ndarray.random()`), it

[GitHub] [incubator-mxnet] xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU.

xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU. URL: https://github.com/apache/incubator-mxnet/issues/15928#issuecomment-522209814 Hi @ptrendx , thanks for your reply, according to my discussion with @yzhliu , device-side API is much slower than

[GitHub] [incubator-mxnet] xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU.

xidulu commented on issue #15928: [RFC] A faster version of Gamma sampling on GPU. URL: https://github.com/apache/incubator-mxnet/issues/15928#issuecomment-521933621 > cc @apache/mxnet-committers I think we can gradually refactor current implementation (ndarray api) by adopting this new