Cuda Error Out Of Memory In Culaunchgrid
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Cuda Error Out Of Memory In Cumemalloc(&device_pointer Size)
Row Forum Support Technical Support CUDA error:Out of memory only in blender 2.65 Results 1 to 4 of 4 Thread: CUDA error:Out of memory only in blender 2.65 Thread Tools Show Printable Version Email this Page… Search Thread
Cuda Out Of Memory Blender
Advanced Search 12-Dec-12,09:40 #1 bls View Profile View Forum Posts Private Message Visit Homepage Member Join Date Oct 2009 Location Athens,Greece Posts 184 CUDA error:Out of memory only in blender 2.65 Hi guys as title says sometimes when working in a scene I have this error when I switch to rendered viewport: "CUDA error: Out of memory in cuLaunchGrid(cuPathTrace,xblocks,yblocks)" Sometimes works but sometimes doesn't. The other weird thing it's that when I hit f12 to render it cuda out of memory error renders just fine. This problem is only in 2.65 version. I tested it in windows 8 64bit and in fedora 17 64bit. Anyone else has this issue? 13-Jan-13,12:40 #2 DrPuzzled View Profile View Forum Posts Private Message Member Join Date Dec 2012 Posts 2 I have the same problem, exept my error message is just a little different. "CUDA error: Out of memory in cuArrayCreate(&handle, &desc)" "CUDA error: Invalid value in cuMemcpy2D(¶m)" It is still an out of memory error though. I can't even do a regular render. If I change the render device to cpu, I can see the rendered veiwport, but I still can't render an image. I am running Linux Mint 14, and have an NVidia GTS 450 with 1GB VRam 17-Jan-13,18:45 #3 cornell View Profile View Forum Posts Private Message Member Join Date Sep 2007 Posts 123 I have the same problem as bls with version 2.65a 64 bit. Running on Ubuntu/Kubuntu with an Nvidia Geforce FTX 260. Rendering with F12 works fine. 08-Apr-13,18:15 #4 Dron09 View Profile View Forum Posts Private Message Member Join Date Jul 2011 Posts 7 The Same Linux mint 14 x64 GTX570 1280mb Older versions of blender has no this problem « Previous Thread | Next Thread » Forum Support Technical Support CUDA error:Out of memory only in blender 2.65 Bookmarks Bookmarks Blender Artists Facebook Group Blender Nation Blender Cookie P
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Blender Out Of Memory In Culaunchkernel
BuildbotInfrastructure: Blender CloudInfrastructure: Blender ConferenceInfrastructure: Blender Foundation cumemgetinfo Certified TrainersInfrastructure: Blender IDInfrastructure: Blender StoreInfrastructure: Blender Web AssetsInfrastructure: Blender.OrgInfrastructure: blender tile size WebsitesLibmvMaskingMesh ModelingModeratorsModifiersMotion TrackingNodesOpenGL / GfxPhysicsPillarPillar Python SDKPillar ServerPillar WebPillar WebsitePlatform: FreeBSDPlatform: LinuxPlatform: Mac OS XPlatform: WindowsPythonQuick HacksRenderingSculpting https://blenderartists.org/forum/showthread.php?274989-CUDA-error-Out-of-memory-only-in-blender-2-65 and PaintingText EditorTranslationsUser InterfaceVideo SequencerQueriesOpen TasksAll TasksSearchAdvanced SearchActionsManiphest HelpManiphest HelpQuick ActionsQuick ActionsLog InLog InSearchCreate TaskCreate FormCreate PasteCreate ProjectEmail HelpEmail Commands: Tasks Maniphest T44504 CUDA ERROR: Out of memory in cuLaunchKernel when rendering on https://developer.blender.org/T44504 GPU GTX 580 Branched Path Tracing / probably sm_20 issueClosed, ArchivedPublicActionsEdit TaskEdit Related Tasks...Edit Parent TasksEdit SubtasksMerge Duplicates InClose As DuplicateEdit Related Objects...Edit CommitsEdit RevisionsSubscribeAward TokenTagsBF Blender (Backlog)SubscribersMarek Dlugajczyk (mdpdesign.pl), Sergey Sharybin (sergey), Bastien Montagne (mont29)Assigned ToSergey Sharybin (sergey)Authored ByMarek Dlugajczyk (mdpdesign.pl), Apr 24 2015DescriptionSystem Information Windows 7 x64, OS X 10.9, OS X 10.10.3, GPU: GTX 580 1,5GB + GTS 450 1GB - OS independent Blender Version Broken: 2.74-000dfc0 official release, 2.74-9e9a3cb, 2.73a-bbf09d9 Worked: 2.69 r60995 Short description of error CUDA ERROR: Out of memory in cuLaunchKernel when rendering on GPU GTX 580 1,5GB and using Branched Pat
→ Blender → cycles + SSE2 Download! ~24MB » cycles + SSE2 Updated 22:10 May 13th, 2011 XercesBlue 20 (3952) 15,181 Windows 32 Bit Experimental Optimized Blender Hash 36676 This is an experimental win32 SSE2 build with CPU/CUDA http://graphicall.org/blender/experimental?keywords=36676 support. Make sure you have up to date drivers or you won't see the 'GPU' http://stackoverflow.com/questions/7584965/out-of-resources-error-while-doing-loop-unrolling Device! Tested with NVIDIA drivers 270.61 Have Fun! -XercesBlue Tweet this build! Download! ~24MB 20 Comments so far. Leave yours. 09:48 September 18th, 2011 20 . baka_at @daeus Had the same issue while working on complicated scene and using nVidia GeForce 320M, what kind of scene you're trying to render ? Could you try to render standard cube and see out of if that solves the trick ? In my case I assume that at first scene was too complex to fit into 256MB of mem that GF 320M operates on. Try it yourself 01:14 May 18th, 2011 19 . daeuss Can't find an edit button sorry. I mean the 64 bit version of cycles does the same for me. 01:10 May 18th, 2011 18 . daeuss CPU mode works fine for me but GPU mode just gives me a black out of memory screen. The console reports CUDA error: Out of memory in cuLaunchGrid(cuPathTrace, xblocks, yblocks) Athlon x2 3.2 8800GTS 320 Vista 64 I've installed 270.61, Cuda Toolkit 4 64 and 32 The 32 bit SSE2 version does the same for me. Any thoughts? 03:42 May 14th, 2011 17 . pistoltoto the same! I did tests on the performance CPU and GPU I realized that when you use GPU cycles is less than 35% processor use And when using the CPU, processor using 90% -95% Why not use processor cycles within 90% with GPU? and Thanks for the cycles. Look at the video: http://youtu.be/1UfZMSIsUDc?hd=1 15:01 May 12th, 2011 16 . Moolah @Vyache01 You need to use it with Fresnel lower than 0.45 (0.15 is very close to glass). 09:38 May 7th, 2011 15 . Vyache01 Reflection isn't looking right, I'm using Glass BSDF with roughness at nil and Frensel at around 0.600 and up. 00:50 May 7th, 2011 14 . gbarctic Nice... made a test (for info, downloaded to a x64 i7, Nvidia 1.5gb, 8gb ram). Used this startup scene (with some new settings. Rendered with 100 Passess Render with CPU: 1 minute 44 sec Render with GPU: 40 sec :-) 13:37 May 6th, 2011 13 . KyungSoo Can Cycles support Muti GPUs mode ? 09:18 May 5th, 2011 12 . test1 Thanks! does this have the animation patch? I cant get animation to work. [bf-
here for a quick overview of the site Help Center Detailed answers to any questions you might have Meta Discuss the workings and policies of this site About Us Learn more about Stack Overflow the company Business Learn more about hiring developers or posting ads with us Stack Overflow Questions Jobs Documentation Tags Users Badges Ask Question x Dismiss Join the Stack Overflow Community Stack Overflow is a community of 4.7 million programmers, just like you, helping each other. Join them; it only takes a minute: Sign up `Out of resources` error while doing loop unrolling up vote 4 down vote favorite When I increase the unrolling from 8 to 9 loops in my kernel, it breaks with an out of resources error. I read in How do I diagnose a CUDA launch failure due to being out of resources? that a mismatch of parameters and an overuse of registers could be a problem, but that seems not be the case here. My kernel calculates the distance between n points and m centroids and selects for each point the closest centroid. It works for 8 dimensions but not for 9. When I set dimensions=9 and uncomment the two lines for the distance calculation, I get an pycuda._driver.LaunchError: cuLaunchGrid failed: launch out of resources. What do you think, could cause this behavior? What other iusses can cause an out of resources*? I use an Quadro FX580. Here is the minimal(ish) example. For the unrolling in the real code I use templates. import numpy as np from pycuda import driver, compiler, gpuarray, tools import pycuda.autoinit ## preference np.random.seed(20) points = 512 dimensions = 8 nclusters = 1 ## init data data = np.random.randn(points,dimensions).astype(np.float32) clusters = data[:nclusters] ## init cuda kernel_code = """ // the kernel definition __device__ __constant__ float centroids[16384]; __global__ void kmeans_kernel(float *idata,float *g_centroids, int * cluster, float *min_dist, int numClusters, int numDim) { int valindex