Returns the number of installed CUDA-enabled devices.
Use this function before any other CUDA functions calls. If OpenCV is compiled without CUDA support, this function returns 0.
Sets a device and initializes it for the current thread.
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If the call of this function is omitted, a default device is initialized at the fist CUDA usage.
Returns the current device index set by cuda::setDevice() or initialized by default.
Explicitly destroys and cleans up all resources associated with the current device in the current process.
Any subsequent API call to this device will reinitialize the device.
Enumeration providing CUDA computing features.
Class providing a set of static methods to check what NVIDIA* card architecture the CUDA module was built for.
The following method checks whether the module was built with the support of the given feature:
- C++: static bool cuda::TargetArchs::builtWith(FeatureSet feature_set)¶
Parameters:
- feature_set – Features to be checked. See cuda::FeatureSet.
There is a set of methods to check whether the module contains intermediate (PTX) or binary CUDA code for the given architecture(s):
- C++: static bool cuda::TargetArchs::has(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasPtx(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasBin(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasEqualOrLessPtx(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasEqualOrGreater(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasEqualOrGreaterPtx(int major, int minor)¶
- C++: static bool cuda::TargetArchs::hasEqualOrGreaterBin(int major, int minor)¶
Parameters:
- major – Major compute capability version.
- minor – Minor compute capability version.
According to the CUDA C Programming Guide Version 3.2: “PTX code produced for some specific compute capability can always be compiled to binary code of greater or equal compute capability”.
Class providing functionality for querying the specified GPU properties.
class CV_EXPORTS DeviceInfo
{
public:
//! creates DeviceInfo object for the current GPU
DeviceInfo();
//! creates DeviceInfo object for the given GPU
DeviceInfo(int device_id);
//! ASCII string identifying device
const char* name() const;
//! global memory available on device in bytes
size_t totalGlobalMem() const;
//! shared memory available per block in bytes
size_t sharedMemPerBlock() const;
//! 32-bit registers available per block
int regsPerBlock() const;
//! warp size in threads
int warpSize() const;
//! maximum pitch in bytes allowed by memory copies
size_t memPitch() const;
//! maximum number of threads per block
int maxThreadsPerBlock() const;
//! maximum size of each dimension of a block
Vec3i maxThreadsDim() const;
//! maximum size of each dimension of a grid
Vec3i maxGridSize() const;
//! clock frequency in kilohertz
int clockRate() const;
//! constant memory available on device in bytes
size_t totalConstMem() const;
//! major compute capability
int majorVersion() const;
//! minor compute capability
int minorVersion() const;
//! alignment requirement for textures
size_t textureAlignment() const;
//! pitch alignment requirement for texture references bound to pitched memory
size_t texturePitchAlignment() const;
//! number of multiprocessors on device
int multiProcessorCount() const;
//! specified whether there is a run time limit on kernels
bool kernelExecTimeoutEnabled() const;
//! device is integrated as opposed to discrete
bool integrated() const;
//! device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer
bool canMapHostMemory() const;
enum ComputeMode
{
ComputeModeDefault, /**< default compute mode (Multiple threads can use ::cudaSetDevice() with this device) */
ComputeModeExclusive, /**< compute-exclusive-thread mode (Only one thread in one process will be able to use ::cudaSetDevice() with this device) */
ComputeModeProhibited, /**< compute-prohibited mode (No threads can use ::cudaSetDevice() with this device) */
ComputeModeExclusiveProcess /**< compute-exclusive-process mode (Many threads in one process will be able to use ::cudaSetDevice() with this device) */
};
//! compute mode
ComputeMode computeMode() const;
//! maximum 1D texture size
int maxTexture1D() const;
//! maximum 1D mipmapped texture size
int maxTexture1DMipmap() const;
//! maximum size for 1D textures bound to linear memory
int maxTexture1DLinear() const;
//! maximum 2D texture dimensions
Vec2i maxTexture2D() const;
//! maximum 2D mipmapped texture dimensions
Vec2i maxTexture2DMipmap() const;
//! maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory
Vec3i maxTexture2DLinear() const;
//! maximum 2D texture dimensions if texture gather operations have to be performed
Vec2i maxTexture2DGather() const;
//! maximum 3D texture dimensions
Vec3i maxTexture3D() const;
//! maximum Cubemap texture dimensions
int maxTextureCubemap() const;
//! maximum 1D layered texture dimensions
Vec2i maxTexture1DLayered() const;
//! maximum 2D layered texture dimensions
Vec3i maxTexture2DLayered() const;
//! maximum Cubemap layered texture dimensions
Vec2i maxTextureCubemapLayered() const;
//! maximum 1D surface size
int maxSurface1D() const;
//! maximum 2D surface dimensions
Vec2i maxSurface2D() const;
//! maximum 3D surface dimensions
Vec3i maxSurface3D() const;
//! maximum 1D layered surface dimensions
Vec2i maxSurface1DLayered() const;
//! maximum 2D layered surface dimensions
Vec3i maxSurface2DLayered() const;
//! maximum Cubemap surface dimensions
int maxSurfaceCubemap() const;
//! maximum Cubemap layered surface dimensions
Vec2i maxSurfaceCubemapLayered() const;
//! alignment requirements for surfaces
size_t surfaceAlignment() const;
//! device can possibly execute multiple kernels concurrently
bool concurrentKernels() const;
//! device has ECC support enabled
bool ECCEnabled() const;
//! PCI bus ID of the device
int pciBusID() const;
//! PCI device ID of the device
int pciDeviceID() const;
//! PCI domain ID of the device
int pciDomainID() const;
//! true if device is a Tesla device using TCC driver, false otherwise
bool tccDriver() const;
//! number of asynchronous engines
int asyncEngineCount() const;
//! device shares a unified address space with the host
bool unifiedAddressing() const;
//! peak memory clock frequency in kilohertz
int memoryClockRate() const;
//! global memory bus width in bits
int memoryBusWidth() const;
//! size of L2 cache in bytes
int l2CacheSize() const;
//! maximum resident threads per multiprocessor
int maxThreadsPerMultiProcessor() const;
//! gets free and total device memory
void queryMemory(size_t& totalMemory, size_t& freeMemory) const;
size_t freeMemory() const;
size_t totalMemory() const;
//! checks whether device supports the given feature
bool supports(FeatureSet feature_set) const;
//! checks whether the CUDA module can be run on the given device
bool isCompatible() const;
};
The constructors.
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Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it constructs an object for the current device.
Returns the major compute capability version.
Returns the minor compute capability version.
Returns the amount of free memory in bytes.
Returns the amount of total memory in bytes.
Provides information on CUDA feature support.
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This function returns true if the device has the specified CUDA feature. Otherwise, it returns false .