Hi Richard, The first part was smooth. I got it done pretty quickly (installing CUDA and setting it up!). However for the freesurfer portion I have two questions,
1. Bruce mentioned in another email thread that v6 beta should be out in a week or so after testing is completed. Should I wait for that version, assuming I get the source code for v6 when I download it as per the instructions on the freesurfer page. 2. Also, would I have to compile and build all modules (mri_em_registe, mri_ca_register etc or can I limit to just these two when I build it again. I'm not very well versed with the second part and so if you could explain a little more it will be good. Thanks, Tyson On Mon, Mar 7, 2016 at 6:38 PM, R Edgar <freesurfer....@gmail.com> wrote: > On 7 March 2016 at 11:25, Francis Tyson Thomas > <francisttho...@email.arizona.edu> wrote: > > > That information was a lot helpful. At this point I'm currently trying to > > reduce the recon-all processing time as much as possible and for this > reason > > I was looking to get the -use-gpu flag working. I'm currently running a > > freesurfer v6 beta version on Ubuntu 14.04.4. With regard to the graphic > > card it is a dual K2200 configuration (I guess they are running in sli > > configuration - although I'm not completely sure). > > > > When you mentioned you compiled everything, I believe you were referring > to > > compiling CUDA 7.5 for Ubuntu 14.04. Because after seeing the link - > > https://developer.nvidia.com/cuda-gpus > > - we settled for CUDA 5 since it was the compatible version mentioned > for > > K2200. Does that mean CUDA 7.5 is backwards compatible with a slight > > tinkering and can be used with freesurfer 6.0 ? > > I think that you might have misunderstood the NVIDIA page. > > It lists the K2200 as a Compute Capability 5 GPU (just like my K1200). > The Compute Capability refers to the hardware: > > http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#compute-capabilities > Compute capability 5 is also called "Maxwell," while the work I did on > Freesurfer was around the time of Compute Capability 2, known as > Fermi. In CPU terms, GPU compute capabilities are a bit like Ivy > Bridge vs Sandy Bridge (although I think that GPU features vary more > than the CPU ones). > > In order to program the GPU, you need the NVIDIA CUDA Toolkit, which > contains the required compiler (nvcc). The current version of this is > 7.5. I installed it by following the instructions on NVIDIA's website: > http://docs.nvidia.com/cuda/index.html > This was quite straightforward (certainly moreso than it was five or > six years ago, when you could never be sure that your X11.conf would > survive). > > Either with the toolkit, or as a separate install, you can get a lot > of examples from NVIDIA. I'd suggest grabbing those, and making sure > that you can compile them. The "DeviceQuery" one will probe your PCIe > bus, and report what GPUs it finds. > > > I however tried to setup CUDA 5 following the instructions in the link - > > http://www.unixmen.com/how-to-install-cuda-5-0-toolkit-in-ubuntu/ - > however, > > I'm not able to get it running. I keep getting the following error > "Unable > > to acquire CUDA device". Does this sound familiar ? > > I suspect (although I wasn't following things at the time) that the > Toolkit v5 was before Maxwell cards were released. If so, then it > wouldn't know what to do with the GPUs. > > For the record, since I was writing the CUDA bits so long ago (for the > volume side of things - I didn't do the surface accelerations), they > only use Fermi features. For this reason, you'll want to make sure > that you have --enable-fermi-gpu when you run configure (and make sure > that it's picking out your CUDA installation - I had to tweak the > configure script for this). > > > If you can share some more information in setting this up it will be > great > > since the amount of time recon-all takes is quite too long for running > > multiple datasets. Most importantly we are concerned about the > hippocampal > > segmentation in freesurfer 6 rather than recon-all and so speeding this > up > > would be extremely helpful. > > I don't know if those portions benefit from CUDA acceleration at this > time. I focused on mri_em_register and mri_ca_register. Even if other > programs (which ones are they?) can be linked against some of the > accelerated routines, there is no guarantee of speed up - the time to > shuffle data to and from the GPU is typically greater than the speedup > of any one routine. > > Hope this helps, > > Richard > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to whom it > is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > >
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