The CUDA (Compute Unified Device Architecture) SDK can be used to write programms running on NVIDIA GPUs. Most workstations in CIP2 have CUDA installed, the workstations have aliases "cuda1"-"cuda7".
These machines are used for the CUDA seminar that is usually offered in the summer semester.
We have one GeForce GT 1050 with CUDA capability 6.1, a GeForce GTX 960 with CUDA capability 5.2, a GeForce GTX 780 with CUDA capability 3.5, a GeForce GT 640 with CUDA capability 3.0 and a couple of others.
Host | Alias | Card
cip2coffee | cuda1 | GeForce GT 1050
cip2sandy1 | cuda2 | GeForce GT 960
cip2sandy2 | cuda3 | GeForce GT 780
cip2sandy3 | cuda4 | GeForce GT 470
cip2skylake1 | cuda5 | GeForce GT 640
cip2smart | cuda6 | GeForce GT 210
cip1ivy | cuda7 | GeForce 1050 Ti
cont3iseven1 | X | GeForce GT 630 (these older cards will be removed)
cont3iseven2 | X | GeForce GT 710
cont3iseven3 | X | GeForce GT 560 Ti
You can find out about the CUDA capabilities of the card in your workstation with the deviceQuery program from the samples directory:
gi32rog@cip2sandy2:~$ /mount/share/cuda-samples/1_Utilities/deviceQuery/deviceQuery /mount/share/cuda-samples/1_Utilities/deviceQuery/deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "GeForce GTX 560 Ti" CUDA Driver Version / Runtime Version 6.5 / 6.5 CUDA Capability Major/Minor version number: 2.1 Total amount of global memory: 2047 MBytes (2146631680 bytes) ( 8) Multiprocessors, ( 48) CUDA Cores/MP: 384 CUDA Cores GPU Clock rate: 1645 MHz (1.64 GHz) Memory Clock rate: 2004 Mhz Memory Bus Width: 256-bit L2 Cache Size: 524288 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65535), 3D=(2048, 2048, 2048) Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 32768 Warp size: 32 Maximum number of threads per multiprocessor: 1536 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (65535, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 1 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device PCI Bus ID / PCI location ID: 1 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 6.5, CUDA Runtime Version = 6.5, NumDevs = 1, Device0 = GeForce GTX 560 Ti Result = PASS
Local users can also try the graphical examples in /mount/share/cuda-samples, there are the binaries, the source code and quite a lot of documentation. Compiling your own programs has become a lot easier since CUDA5, in the past we needed to make lots of modifications to the Makefiles, but now there are just a few changes. After you have copied the source files to your home directory, change the line
INCLUDES := -I$(CUDA_INC_PATH) -I. -I.. -I../../common/inc
INCLUDES := -I$(CUDA_INC_PATH) -I. -I.. -I$(CUDA_PATH)/samples/common/inc
(necessary because the includes of the samples are in the cuda tree, not in your HOME.) Also, you should comment out (or delete) the lines that make a copy of the finished binary,
# mkdir -p ../../bin/$(OSLOWER)/$(TARGET) # cp $@ ../../bin/$(OSLOWER)/$(TARGET)
This way you should be able to compile everything by typing make. (If you are compiling some of the graphical examples, you also need to replace
Excellent Documentation is available at the NVIDIA homepage. You should check out this extensive site. But for starters it should be enough to read Getting_Started. Last but not least, don't forget to checkout the webinars.