Is This A GPU Or Network Problem?
Your code would then work much in the same way as it does on a multi-core system, just keep in mind that each core then has 32 threads of its own. I am using Windows Server 2012 Datacenter, Python 2.7.10 x64. gpapadop79 commented Feb 16, 2016 I also ran matrixMulCUBLAS and it passes. with __synchtreads()). –Pedro Jan 23 '12 at 23:33 @Pedro: True, but branching in general does hurt performance. Source
On Sun, Mar 6, 2016 at 11:49 PM, xenmind [email protected] wrote: Hi, Installed the GPU enabled R library (R version: 3.2.3) on Windows 7 today. Not the answer you're looking for? I'm using a 2.1 GPU. Thanks, Gavin. http://www.tomshardware.com/forum/374150-33-internet-connection-problems-graphics-card-change
New Graphics Card No Internet Connection
Galaxy S8: Clash of the Titans (Rumors) How to Stop Netflix From Auto-Playing the Next Episode Tom’s guide in the world Germany France Italy Ireland UK About Us | Contact Us If you'd like a code example, let me know and I'll post one. –Pedro Jan 23 '12 at 22:51 add a comment| up vote 5 down vote From a metaphorical point Now xfwm4 relies upon glx backend, which fix tearing and may fix problems with your gpu. But I don't have another Windows 10/8/7 machine to test on.
I really need a solution Member hjk41 commented Nov 10, 2016 To build MxNet from source, please follow the instructions here: http://mxnet.io/get_started/setup.html#build-mxnet-on-windows The prebuilt binary sometimes have strange problems with different For example, on AMD cards if any of the instruction flows encounters a branch and must diverge - all the wavefront (parallel group) diverges. thyu commented Feb 23, 2016 The new release works on my machine as well, awesome! Member hjk41 commented Mar 7, 2016 I haven't tested it on GPU with with compute capability 2.1.
Does this also occur for low compute capability GPUs on Linux? Why do people do postdocs rather than become a professor, assuming a PhD trains them in how to do research? done Performance= 4.40 GFlop/s, Time= 29.805 msec, Size= 131072000 Ops, WorkgroupSize = 1024 threads/block Checking computed result for correctness: Result = PASS NOTE: The CUDA Samples are not meant for performance So, coalesce the storage to increase locality of usage.
Unpredictable problems have too many meaningful branches, which can prevent data from efficiently streaming from GPU memory to the cores or reduce parallelism by breaking the SIMD paradigm (see 'divergent warps'). There is one thing to note that it requires cudnn64_4.dll which belongs to cuDNNv4. I'm using a 2.1 GPU. wdx04 commented Jun 12, 2016 Hi @juanlp , You may download my version of libmxnet.dll here(built on 5/22): http://pan.baidu.com/s/1bzxnvK I'm facing compiling errors with the latest source so I can't provide
Share Can't find your answer ? howard0su referenced this issue Dec 20, 2016 Closed train_mnist give different result between two runs #4306 Sign up for free to join this conversation on GitHub. New Graphics Card No Internet Connection Count the times a digit has appeared in a list as I scan the list Smiley Face using parametric equations Does the Fairchild Metroliner have any unusual handling characteristics? Internet Speed Test Reply to this email directly, view it on GitHub #1228 (comment), or mute the thread https://github.com/notifications/unsubscribe-auth/ABFI4Zv4-sAyjuVyF59GgkeqUHK0w9K-ks5q8ZcYgaJpZM4HBwc2 .
For Ubuntu I just downloaded the latest version and build it. http://goinsource.com/is-this/is-this-a-hardware-problem.html Reverted to the 20160223 build and it works, 0.9911 on MNIST. All nails are in a regular pattern, like a grid. DId anyone know the reason ?
share|cite|improve this answer answered May 27 '13 at 23:01 Brian Borchers 10.5k11435 I want to disagree. Quares commented Feb 1, 2016 This post reports on the same issue: https://www.kaggle.com/c/second-annual-data-science-bowl/forums/t/18079/end-to-end-deep-learning-tutorial-0-0392/105458#post105458 I ran into the same situation as well. jonathanponce commented Mar 22, 2016 The error is back in the latest release the accuracy remain terrible, the 20160223 build works fine, but the rest appear to have the error again
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Anaconda is brought to you by Continuum Analytics. With each SM designed to run up to 32 threads in parallel maximizing GPU performance would require keeping the working set in the 1kb/thread range. –Dan Neely Jan 23 '12 at gpu share|cite|improve this question asked Jan 23 '12 at 3:34 Fomite 1,17311121 add a comment| 9 Answers 9 active oldest votes up vote 48 down vote accepted GPU hardware has two Release version still fails with mx.nd.ones, but the debug version works.
I thought the on die memory was only allocated at the cluster of core level not per individual core. I went and downloaded the drivers needed and installed them. xenmind commented Mar 6, 2016 Hi, Installed the GPU enabled R library (R version: 3.2.3) on Windows 7 today. http://goinsource.com/is-this/is-this-a-serious-difficult-problem.html I will try to switch to some other platform and see if it works there.
An attempt to generalize the previous inequality Why is populism seen as being negative or bad? I'm using the latest files for everything, and the precompiled GPU package for R. I also notice that even if I put nothing under 3rdparty\cudnn 20160223_win10_x64_gpu, it still runs, but the gpu ones function returns 0. The global memory of the graphics card (usually 1GB) is accessible by all processing units.
What was the origin of the name "Robin" in the English version of Batman - Dark Victory? It also is taken to mean that your data access patterns can be predetermined either by the compiler somehow or by you the programmer so that branching (conditional statements in code) Till now I was under the impression that only v3 is supported. Different warps, although executing the same code, are not synchronous unless explicitly synchronized (e.g.
Windows Server 2012 and Windows 10/8 uses different CUDA binaries so I assume there is some difference between the libraries we link. The error has been fixed. Thanks, Gavin. — Reply to this email directly or view it on GitHub #1228 (comment).