Example Path: %NVCUDASAMPLES_ROOT%\1_Utilities\deviceQueryDrv
The NVIDIA CUDA Example Device Query shows how to discovery GPGPU's on the host and how to discover their capabilities.
The basic execution looks like the following for a Geforce GT650M card in an HP Pavilion dv6 Laptop:
deviceQuery.exe Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "GeForce GT 650M" CUDA Driver Version / Runtime Version 6.5 / 6.5 CUDA Capability Major/Minor version number: 3.0 Total amount of global memory: 1024 MBytes (1073741824 bytes) ( 2) Multiprocessors, (192) CUDA Cores/MP: 384 CUDA Cores GPU Clock rate: 835 MHz (0.83 GHz) Memory Clock rate: 2000 Mhz Memory Bus Width: 128-bit L2 Cache Size: 262144 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096) 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: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 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): (2147483647, 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 CUDA Device Driver Mode (TCC or WDDM): WDDM (Windows Display Driver Mo del) 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 simu ltaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 6.5, CUDA Runtime Versi on = 6.5, NumDevs = 1, Device0 = GeForce GT 650M Result = PASS
The example first discovers the number of devices using cuDeviceGetCount(..) and then iterates over g a host of capability discovery functions such as:
Where the bulk of the attributes are retrieved with getCudaAttribute using an enumerated selector to return the right value as in:
int asyncEngineCount; getCudaAttribute<int>(&asyncEngineCount, CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT, dev);
And if there are more than two devices it checks to see if RDMA is enabled between them.