To put it a little differently: the GPU architecture has been developed around video games. In a video game architecture, you have a fairly small amount of data (models and textures) going into the GPU memory via the bus, and then a lot of data coming out of the GPU hardware substrate to the video output.
The bus architecture is not designed to shovel a lot of data into the GPU memory, and I don't know how good they are about pushing data out to system memory. So you want problems where a "relatively" small amount of data has to be chewed over heavily (without building up numerical error). There are some like this- stock market quants for example. On Sun, Jul 8, 2012 at 4:21 PM, Ted Dunning <[email protected]> wrote: > In general, large scale machine learning is I/O bound already. There are > some things that would not be, but to really feed a GPU reasonably, data > almost has to be memory resident. > > For more information on CUDA from Java, see (among others) > http://www.jcuda.de/ > > On Sun, Jul 8, 2012 at 4:04 PM, Sean Owen <[email protected]> wrote: > >> More than that, Mahout is mostly Hadoop-based, which is well up the >> stack from Java. No there is nothing CUDA-related in the project. The >> closest thing are the pure Java non-Hadoop-based recommender pieces. >> But it is still far from CUDA. >> >> I think CUDA is intriguing since a lot of ML is a bunch of matrix math >> and GPUs are very good at vectorized math. I think a first step is to >> introduce proper JNI bindings for the big matrix math jobs and see how >> much that gains. If it's a lot, then CUDA-izing the JNI pieces is an >> interesting next step. >> >> On Sun, Jul 8, 2012 at 11:41 PM, mohsen jadidi <[email protected]> >> wrote: >> > Hello , >> > >> > This is my first post here and I just started reading about Hadoop, >> Mahout >> > and all. I was wondering if there is any solution to use Mahout on >> parallel >> > computing on GPU (mainly CUDA) ? I know it's a bit wired question to ask >> > because cud a is C base and Mahout is Java base , but I just ask it as >> > curiosity! I think it would be a very cool combination to use both >> cluster >> > and local parallelisation ! >> > >> > cheers, >> > -- >> > Mohsen >> -- Lance Norskog [email protected]
