#Nvidia quadro k600 vs 1030 upgrade#
#Nvidia quadro k600 vs 1030 code#

My problem is difference between 2 cards - so as I said before if I can get some official links regarding this вЂњwell be changed by moving to a different GPUвЂќ then it will be very helpful. Regarding the difference in results - let me just confirm one thing here my results always come same when it is done in K620 card, so this. So are you absolutely sure that it canвЂ™t be done in CUDA toolkit 4.0 + VS 2008 combination ? Now the requirement is to support K620 (Maxwell) - and I want to build it in a way so that it can use the Maxwell card properly.

#Nvidia quadro k600 vs 1030 code#

This is an old code base so previously also it was not optimized with K600 etc. Maxwell should be supported on toolkit below 5.5Д«y difference in resulting pixels I am referring to this kind of change ->Д«efore K620 my application was running based on sm_21. Sorry if my question was not very clear, I am staring to work on CUDA from this week only.

Use a tool equivalent to the Linux tool valgrind to check for out-of-bounds accesses and uninitialized data in host code. Your problem may also be in the host code. Make sure your application checks the return status of every CUDA, CUBLAS, CUFFT, etc API call, and every kernel launch.Дoes 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.Д¬heck 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 вЂњdefaultвЂќ build rules you refer to.

#Nvidia quadro k600 vs 1030 upgrade#

If possible, I would suggest upgrading to CUDA 6.5 (this may require an upgrade to Visual Studio, I donвЂ™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.