Thanks for the information on building PyOpenCL. All of the instructions worked.
Before I did anything I checked the version of PyOpenCL on Ubuntu 14.04 and it was 2013.2, The windows version was also 2013.2. I tried updating the Ubuntu PyOpenCL to 2015.1 using pip. This did not change the output I am getting. I added some printf's where possible to the code. The results are below. The results are the last 16 or so lines of output from the simulation. As you will see the results from the Windows calculation on the CPU and Cuda GPU calculation on Ubuntu are very close for each step and the final Dose Maximum are nearly the same, given the randomness. The results from the PyOpenCL calculation on the Ubuntu system show the per step values for e0, urn, tdl, sfc, etc. are nearly the same, but the dose at index [31,31,31] is about 1/2 the value of the Windows and Ubuntu CUDA calculations. What is most disturbing is the dose maximum is always nan for the Pyopencl calculation on Linux. Note, the third line from the bottom of each run has nan values for SeSc and SeSr, this is because e0 is 0 at that point but the values ARE not used in getting the dose after this, the variable urn contains the dose that will be added at each step. I have added the code and the test data to my google drive. https://drive.google.com/file/d/0B3lyn1ou1_v2NzRjVlJBMC1POTQ/view?usp=sharing Edit the file eMC-Second-Check-09-14-15.py by changing the variable progdir on line 57 to the folder where the file is located. Make sure the dataset folder 12E10x10Mat is in the same folder as the file. If you just unzip the tar file from google drive the resulting folder contains all the necessary files/folders. The section that is relevant to this discussion is in lines 1490-2160 of the eMC-Second-Check file. To run the simulation "python eMC-Second-Check-09-14-15.py" When the window opens, click "Open File directory" and navigate and double click to select the "12E10x10Mat" folder. Click "Ok" In "Contours to Override" select "PlasticWater", in "Number of e per cell" select "1000", in "Calculation Grid Size" select "2.5", then click "Calc". The file TestSettings.png shows the proper selections and the youtube video https://www.youtube.com/watch?v=Bm968rcdrCU also shows how to run the program (although with a different data set). Reese ********************************* From AMD OpenCL SDK INTEL Xeon CPU Windows e0 = 0.715011 urn= 0.094236 tdl= 0.050000 sfc= 1.000000 SeSc= 1.914332 sfr= 1.000000 SeSr=0.009564 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.619294 urn= 0.095717 tdl= 0.050000 sfc= 1.000000 SeSc= 1.957221 sfr= 1.000000 SeSr=0.008542 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.521433 urn= 0.097861 tdl= 0.050000 sfc= 1.000000 SeSc= 2.022226 sfr= 1.000000 SeSr=0.007546 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.420322 urn= 0.101111 tdl= 0.050000 sfc= 1.000000 SeSc= 2.128243 sfr= 1.000000 SeSr=0.006575 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.313910 urn= 0.106412 tdl= 0.050000 sfc= 1.000000 SeSc= 2.324997 sfr= 1.000000 SeSr=0.005630 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.197660 urn= 0.116250 tdl= 0.050000 sfc= 1.000000 SeSc= 2.804841 sfr= 1.000000 SeSr=0.004718 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.057418 urn= 0.140242 tdl= 0.050000 sfc= 1.000000 SeSc= 5.982077 sfr= 1.000000 SeSr=0.003610 indx= 31 indy= 31 indz=31 dose= 522.330139 e0 = 0.000000 urn= 0.057418 tdl= 0.050000 sfc= 1.000000 SeSc= -nan sfr= 1.000000 SeSr=-nan indx= 31 indy= 31 indz=31 dose= 522.330139 numpy calculated dose3 maximum= 576.792 From CUDA NVIDIA GTX 780 TI e0 = 0.699718 urn= 0.094441 tdl= 0.050000 sfc= 1.000000 SeSc= 1.920174 sfr= 1.000000 SeSr=0.009398 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.603710 urn= 0.096009 tdl= 0.050000 sfc= 1.000000 SeSc= 1.965868 sfr= 1.000000 SeSr=0.008380 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.505416 urn= 0.098293 tdl= 0.050000 sfc= 1.000000 SeSc= 2.035780 sfr= 1.000000 SeSr=0.007388 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.403627 urn= 0101789 tdl= 0.050000 sfc= 1.000000 SeSc= 2.151626 sfr= 1.000000 SeSr=0.006421 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.296046 urn= 0.107581 tdl= 0.050000 sfc= 1.000000 SeSc= 2.373185 sfr= 1.000000 SeSr=0.005481 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.177387 urn= 0.118659 tdl= 0.050000 sfc= 1.000000 SeSc= 2.955496 sfr= 1.000000 SeSr=0.004575 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.029612 urn= 0.147775 tdl= 0.050000 sfc= 1.000000 SeSc= 9.789070 sfr= 1.000000 SeSr=0.002632 indx= 31 indy= 31 indz=31 dose= 546.358154 e0 = 0.000000 urn= 0.029612 tdl= 0.050000 sfc= 1.000000 SeSc= nan sfr= 1.000000 SeSr=nan indx= 31 indy= 31 indz=31 dose= 546.358154 MAX dose= 583.723 From AMD OpenCL SDK INTEL Xeon CPU Linux e0 = 0.714894 urn= 0.094238 tdl= 0.050000 sfc= 1.000000 SeSc= 1.914375 sfr= 1.000000 SeSr=0.009563 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.619175 urn= 0.095719 tdl= 0.050000 sfc= 1.000000 SeSc= 1.957285 sfr= 1.000000 SeSr=0.008541 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.521311 urn= 0.097864 tdl= 0.050000 sfc= 1.000000 SeSc= 2.022326 sfr= 1.000000 SeSr=0.007545 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.420195 urn= 0.101116 tdl= 0.050000 sfc= 1.000000 SeSc= 2.128413 sfr= 1.000000 SeSr=0.006573 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.313774 urn= 0.106421 tdl= 0.050000 sfc= 1.000000 SeSc= 2.325341 sfr= 1.000000 SeSr=0.005629 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.197507 urn= 0.116267 tdl= 0.050000 sfc= 1.000000 SeSc= 2.805859 sfr= 1.000000 SeSr=0.004717 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.057214 urn= 0.140293 tdl= 0.050000 sfc= 1.000000 SeSc= 5.997465 sfr= 1.000000 SeSr=0.003607 indx= 31 indy= 31 indz=31 dose= 242.133011 e0 = 0.000000 urn= 0.057214 tdl= 0.050000 sfc= 1.000000 SeSc= -nan sfr= 1.000000 SeSr=-nan indx= 31 indy= 31 indz=31 dose= 242.133011 numpy calculated dose3 maximum= nan From INTEL OpenCL SDK INTEL CPU Linux e0 = 0.717825 urn= 0.094179 tdl= 0.050000 sfc= 1.000000 SeSc= 1.913324 sfr= 1.000000 SeSr=0.009595 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.622158 urn= 0.095643 tdl= 0.050000 sfc= 1.000000 SeSc= 1.955667 sfr= 1.000000 SeSr=0.008573 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.524375 urn= 0.097759 tdl= 0.050000 sfc= 1.000000 SeSc= 2.019843 sfr= 1.000000 SeSr=0.007575 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.423383 urn= 0.100967 tdl= 0.050000 sfc= 1.000000 SeSc= 2.124244 sfr= 1.000000 SeSr=0.006603 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.317171 urn= 0.106186 tdl= 0.050000 sfc= 1.000000 SeSc= 2.316915 sfr= 1.000000 SeSr=0.005657 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.201325 urn= 0.115817 tdl= 0.050000 sfc= 1.000000 SeSc= 2.780827 sfr= 1.000000 SeSr=0.004745 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.062284 urn= 0.139007 tdl= 0.050000 sfc= 1.000000 SeSc= 5.642349 sfr= 1.000000 SeSr=0.003689 indx= 31 indy= 31 indz=31 dose= 253.760727 e0 = 0.000000 urn= 0.062269 tdl= 0.050000 sfc= 1.000000 SeSc= -nan sfr= 1.000000 SeSr=-nan indx= 31 indy= 31 indz=31 dose= 253.760727 numpy calculated dose3 maximum= nan From NVIDIA OpenCL NVIDIA GPU Cannot printf in the kernel on the GPU numpy calculated dose3 maximum= nan Confidentiality Notice: This e-mail, including any 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