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Your problem may also be in the host code.
#Nvidia quadro k600 used code#
Make sure your application checks the return status of every CUDA, CUBLAS, CUFFT, etc API call, and every kernel launch.ĭoes your code using floating-point atomics? Since floating-point arithmetic is not associative, this can cause different results depending on the order in which operations occur, which could well be changed by moving to a different GPU.Ĭheck for race conditions and out-of-bounds accesses in your GPU code with cuda-memcheck. K600 is based on GK107, so sm_30 would be the appropriate target architecture. The compiler default in CUDA 4.0 was to build for an sm_10 target, this is definitely not what you want. I am not sure which “default” build rules you refer to.
#Nvidia quadro k600 used upgrade#
If possible, I would suggest upgrading to CUDA 6.5 (this may require an upgrade to Visual Studio, I don’t think VS2008 is supported anymore). This means what you are relying on JIT compilation of PTX intermediate code into machine code, which can be a source of additional issues such as lower performance. It probably does not even have support for sm_35. You are using a very old CUDA version which certainly has no support for the Maxwell-based K620. Here are some basic things you may want to consider. This kind of debugging can be performed with tools as primitive as a log generated from printf() calls in the code. When I debug such issues I follow the data differences back through the code, until I find where the data first diverges. With so little information about your platform, the application, and the exact nature of the differences it is difficult to even speculate what the root cause for the differences could be. If this is a known thing that there will be difference in floating point calculations between Kepler and Maxwell - then I will be very helpful if some one can share with me the link confirming that. So my client is little concerned about the accuracy part. Problem is the output values are coming little different than the previous one. I am having one image processing related CUDA application which previously was being used with K600 card - recently the hardware is changed to K620.