Adam, what input shapes do you do sort on right now? What axis? This is to help to know which car to optimize.
Fred Le mer. 14 juin 2017 22:03, Victor Campmany <[email protected]> a écrit : > 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. > -- --- 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.
