It is a sampled measurement over a time period. For a given time period, it reports what percentage of time one or more GPU kernel(s) was active (i.e. running). It doesn’t tell you anything about how many SMs were used, or how “busy” the code was, or what it was doing exactly, or in what … Read more
The thread / block layout is described in detail in the CUDA programming guide. In particular, chapter 4 states: The CUDA architecture is built around a scalable array of multithreaded Streaming Multiprocessors (SMs). When a CUDA program on the host CPU invokes a kernel grid, the blocks of the grid are enumerated and distributed to … Read more
At the present time, Intel graphics chips do not support CUDA. It is possible that, in the nearest future, these chips will support OpenCL (which is a standard that is very similar to CUDA), but this is not guaranteed and their current drivers do not support OpenCL either. (There is an Intel OpenCL SDK available, … Read more
Metaphorically speaking ati has a good engine compared to nvidia. But nvidia has a better car 😀 This is mostly because nvidia has invested good amount of its resources (in money and people) to develop important libraries required for scientific computing (BLAS, FFT), and then a good job again in promoting it. This may be … Read more
For nvidia (and amd for that matter) gpus the local memory is divided into memorybanks. Each bank can only address one dataset at a time, so if a halfwarp tries to load/store data from/to the same bank the access has to be serialized (this is a bank conflict). For gt200 gpus there are 16 banks … Read more
Nope, you can’t use CUDA for that. CUDA is limited to NVIDIA hardware. OpenCL would be the best alternative. Khronos itself has a list of resources. As does the StreamComputing.eu website. For your AMD specific resources, you might want to have a look at AMD’s APP SDK page. Note that at this time there are … Read more
Using nvidia-smi should tell you that: bwood@mybox:~$ nvidia-smi Mon Oct 29 12:30:02 2012 +——————————————————+ | NVIDIA-SMI 3.295.41 Driver Version: 295.41 | |——————————-+———————-+———————-+ | Nb. Name | Bus Id Disp. | Volatile ECC SB / DB | | Fan Temp Power Usage /Cap | Memory Usage | GPU Util. Compute M. | |===============================+======================+======================| | 0. GeForce … Read more
For those who are seeking the answer in 2016 (and even 2017) … Disclaimer I’ve failed to emulate GPU after all. It might be possible to use gpuocelot if you satisfy its list of dependencies. I’ve tried to get an emulator for BunsenLabs (Linux 3.16.0-4-686-pae #1 SMP Debian 3.16.7-ckt20-1+deb8u4 (2016-02-29) i686 GNU/Linux). I’ll tell you … Read more
The problem was caused by not setting the CUDA_VISIBLE_DEVICES variable within the shell correctly. To specify CUDA device 1 for example, you would set the CUDA_VISIBLE_DEVICES using export CUDA_VISIBLE_DEVICES=1 or CUDA_VISIBLE_DEVICES=1 ./cuda_executable The former sets the variable for the life of the current shell, the latter only for the lifespan of that particular executable invocation. … Read more
There are two parts to that answer (I wrote it). One part is easy to quantify, the other is more empirical. Hardware Constraints: This is the easy to quantify part. Appendix F of the current CUDA programming guide lists a number of hard limits which limit how many threads per block a kernel launch can … Read more