I attach patch updating pycuda.tools.DeviceData and pycuda.tools.OccupancyRecord to take new devices into consideration. I have tried to maintain "style" of those classes and introduced changes only when necessary. I have done changes using my old notes and NVIDIA Occupancy Calculator. Unfortunately I currently do not have access to Fermi to test those fully.

Dnia 2011-07-29, pią o godzinie 02:15 -0400, Andreas Kloeckner pisze: > Hi Tomasz, > > On Mon, 21 Mar 2011 20:15:35 +0100, "=?UTF-8?B?VG9tYXN6IFJ5YmFr?=" <bogomips(a)post.pl&gt; wrote: > > I attach patch updating pycuda.tools.DeviceData and > > pycuda.tools.OccupancyRecord > > to take new devices into consideration. I have tried to maintain "style" of > > those classes > > and introduced changes only when necessary. I have done changes using my old > > notes > > and NVIDIA Occupancy Calculator. Unfortunately I currently do not have > > access to Fermi > > to test those fully. > > - self.smem_granularity = 16 > + if dev.compute_capability() >= (2,0): > + self.smem_granularity = 128 > + else: > + self.smem_granularity = 512 > > Way back in March, you submitted this patch, where smem_granularity is > documented as the number of threads taking part in a simultaneous smem > access. The new values just seem wrong. What am I missing, or rather, > what did you have in mind? I have taken those values from CUDA_Occupancy_Calculator.xls, from sheet "GPU Data", cells C11-H12. Sorry for mess. It looks like I have misunderstood smem_granularity meaning. I assumed (after xls file) that it was minimum size of shared memory that can be allocated. It looks like that from analysis of source code in OccupancyRecord (tools.py:294): alloc_smem = _int_ceiling(shared_mem, devdata.smem_granularity) If I understand it correctly, it computes amount of allocated shared memory, rounding it to the nearest multiplication of smem_granularity. With such assumptions, my patch makes sense - one can allocate shared memory in block of 512 for 1.x devices, and blocks of 128 for 2.x devices. So I do not understand why there is difference between documentation " .. attribute:: smem_granularity The number of threads that participate in banked, simultaneous access to shared memory." and code, which does not take threads into consideration when dealing with smem_granularity.