The implementation would be for *Gpuarray*, not Theano, I mixed things up sorry.
El miércoles, 14 de junio de 2017, 20:47:41 (UTC-4), Adam Becker escribió: > > I'd prefer a gpuarray implementation with similar interface as numpy: > > gpuarray.sort(arr, [axis=-1], [kind='radixsort'], [order='inc']) > > Deep Learning folks would need a fast batched version, especially float32 > / int32 tensors on GPU. But anyway there should be a general algorithm > deals with all cases, never know what kind of model would come up in > future. > > On Thursday, June 15, 2017 at 4:01:00 AM UTC+8, Victor Campmany wrote: >> >> Hi, >> >> We are planning to implement a new GPU accelerated sorting algorithm. >> We'd like to know which are the most frequent sorting cases that you guys >> use and the data sizes you are dealing with. For example, sorting a large >> 1d array, sorting a given axis of a tensor or minibatch, or any other type >> of sorting you come up with. >> > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
