Hi Dave, Thanks a lot. I will try x10-trunk again.
yeah... I've seen that the text console allows me to go ahead :) Another good reason for Emacs in text mode :D Thanks Richard Gomes M: +44(77)9955-6813 http://tinyurl.com/frgomes twitter: frgomes JQuantLib is a library for Quantitative Finance written in Java. http://www.jquantlib.org/ twitter: jquantlib On 19/11/10 02:34, Dave Cunningham wrote: > I fixed the segfault in trunk recently. This was a null dereference in the > memory freeing code. > > You shouldn't have run out of memory there, it only needs about 80MB iirc > and you have 128. Sometimes all the memory gets tied up in the windowing > system. If you're using linux, switching to the text console and back often > flushes it back out and lets you run CUDA programs again. I'm not sure if > there is an equivalent in windows. > > > On Thu, Nov 11, 2010 at 10:36 PM, Richard Gomes<rgomes1...@yahoo.co.uk>wrote: > >> Hi Igor, >> >> I applied the patch onto SF_RELEASE_2_1_0 and it compiles fine. >> When I run the sample programs, CUDATopology and CUDAKernelTest work >> fine whilst others fail like this: >> >> >> $ runx10 KMeansCUDA >> points: 100000 clusters: 8 dim: 4 >> Running using 1 GPUs. >> GPU known as (Place 1) gets role 0 offset 0 len 100000 >> 100000 8 4 2.703 >> kernel: 1.689 >> dma: 0.447 >> cpu: 0.463 >> reduce: 0.101 >> Segmentation fault >> >> >> >> >> $ runx10 CUDABlackScholes >> Using the GPU at place (Place 1) >> This program only supports a single GPU. >> CUDA_ERROR_OUT_OF_MEMORY (At common/x10rt_cuda.cc:452) >> Aborted >> >> >> >> Are these failures considered 'expected' or my graphics card is not very >> intelligent for such tasks? I have a GeForce 8300 GS >> >> Device 0: "GeForce 8300 GS" >> > CUDA Driver Version: 3.20 >> > CUDA Runtime Version: 3.20 >> > CUDA Capability Major/Minor version number: 1.1 >> > Total amount of global memory: 133496832 bytes >> > Multiprocessors x Cores/MP = Cores: 1 (MP) x 8 (Cores/MP) >> > = 8 (Cores) >> > Total amount of constant memory: 65536 bytes >> > Total amount of shared memory per block: 16384 bytes >> > Total number of registers available per block: 8192 >> > Warp size: 32 >> > Maximum number of threads per block: 512 >> > Maximum sizes of each dimension of a block: 512 x 512 x 64 >> > Maximum sizes of each dimension of a grid: 65535 x 65535 x 1 >> > Maximum memory pitch: 2147483647 bytes >> > Texture alignment: 256 bytes >> > Clock rate: 0.92 GHz >> > Concurrent copy and execution: No >> > Run time limit on kernels: Yes >> > Integrated: No >> > Support host page-locked memory mapping: Yes >> > Compute mode: Default (multiple host >> >> >> Thanks >> >> >> Richard Gomes >> M: +44(77)9955-6813 >> http://tinyurl.com/frgomes >> twitter: frgomes >> >> JQuantLib is a library for Quantitative Finance written in Java. >> http://www.jquantlib.org/ >> twitter: jquantlib >> >> On 09/11/10 22:22, Igor Peshansky wrote: >>> Richard, >>> >>> "svn diff -r18088:18092 x10.runtime/x10rt/common/x10rt_cuda.cc" in our >>> repo should generate that patch. >>> Igor >>> >>> Richard Gomes<rgomes1...@yahoo.co.uk> wrote on 11/09/2010 05:11:43 PM: >>> >>>> Hi Dave, >>>> >>>> Could you please send the patch again? >>>> >>>> Thanks >>>> >>>> Richard Gomes >>>> M: +44(77)9955-6813 >>>> http://tinyurl.com/frgomes >>>> twitter: frgomes >>>> >>>> JQuantLib is a library for Quantitative Finance written in Java. >>>> http://www.jquantlib.org/ >>>> twitter: jquantlib >>>> >>>> On 09/11/10 03:45, Dave Cunningham wrote: >>>>> Thanks for trying out X10/CUDA >>>>> >>>>> Your initial problem with CUDATopology is due to the fact that >>> X10RT_ACCELS >>>>> is ineffective if X10 was built without -DX10RT_CUDA=true, this means >>> the >>>>> X10 application was unable to 'see' the accelerators. You correctly >>>>> surmised that building X10 from the source release was necessary. >>>>> >>>>> The build errors are due to nvidia adding more error codes and making >>>>> backwards incompatible changes in the CUDA API. This is now fixed in >>> SVN. >>>>> I checked the build with the following CUDA versions: >>>>> >>>>> cuda-2.2 cuda-2.3 cuda-3.0 cuda-3.1 cuda-3.2.12 >>>>> >>>>> If you decide to use SVN, there are some changes to the way kernels >>> should >>>>> be written in X10 that are currently undocumented (except via the code >>> in >>>>> the samples dir). Also, we can't guarantee there won't be more >>> changes (and >>>>> breakages) before the next release. However you will be able to try >>> new >>>>> features like clocks and constant memory on the GPU. >>>>> >>>>> If using SVN does not appeal, you can also patch the source release to >>> fix >>>>> this problem. Apply the attached patch from the root of the source >>> release >>>>> as follows, and rebuild: >>>>> >>>>> patch -p0< cuda_3.2.patch >>>>> >>>>> hope this helps >> >> >> ------------------------------------------------------------------------------ >> Centralized Desktop Delivery: Dell and VMware Reference Architecture >> Simplifying enterprise desktop deployment and management using >> Dell EqualLogic storage and VMware View: A highly scalable, end-to-end >> client virtualization framework. Read more! >> http://p.sf.net/sfu/dell-eql-dev2dev >> _______________________________________________ >> X10-users mailing list >> X10-users@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/x10-users >> > ------------------------------------------------------------------------------ > Beautiful is writing same markup. 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