Class cv::cuda::DeviceInfo#

Class providing functionality for querying the specified GPU properties.

#include <opencv2/core/cuda.hpp>

Collaboration diagram for cv::cuda::DeviceInfo:

Public Types#

enum ComputeMode {
    ComputeModeDefault,
    ComputeModeExclusive,
    ComputeModeProhibited,
    ComputeModeExclusiveProcess
}

Detailed Description#

Class providing functionality for querying the specified GPU properties.

Member Enumeration Documentation#

enum ComputeMode

`ComputeModeDefault` Python: `cv.cuda.DeviceInfo_ComputeModeDefault`	default compute mode (Multiple threads can use cudaSetDevice with this device)
`ComputeModeExclusive` Python: `cv.cuda.DeviceInfo_ComputeModeExclusive`	compute-exclusive-thread mode (Only one thread in one process will be able to use cudaSetDevice with this device)
`ComputeModeProhibited` Python: `cv.cuda.DeviceInfo_ComputeModeProhibited`	compute-prohibited mode (No threads can use cudaSetDevice with this device)
`ComputeModeExclusiveProcess` Python: `cv.cuda.DeviceInfo_ComputeModeExclusiveProcess`	compute-exclusive-process mode (Many threads in one process will be able to use cudaSetDevice with this device)

Constructor & Destructor Documentation#

DeviceInfo()#

cv::cuda::DeviceInfo::DeviceInfo()

Python:

cv.cuda.DeviceInfo() -> <cuda_DeviceInfo object>

cv.cuda.DeviceInfo(device_id) -> <cuda_DeviceInfo object>

creates DeviceInfo object for the current GPU

DeviceInfo()#

cv::cuda::DeviceInfo::DeviceInfo(int device_id)

Python:

cv.cuda.DeviceInfo() -> <cuda_DeviceInfo object>

cv.cuda.DeviceInfo(device_id) -> <cuda_DeviceInfo object>

The constructors.

Constructs the DeviceInfo object for the specified device. If device_id parameter is missed, it constructs an object for the current device.

Parameters

device_id — System index of the CUDA device starting with 0.

Member Function Documentation#

asyncEngineCount()#

int cv::cuda::DeviceInfo::asyncEngineCount()

Python:

cv.cuda.DeviceInfo.asyncEngineCount() -> retval

number of asynchronous engines

canMapHostMemory()#

bool cv::cuda::DeviceInfo::canMapHostMemory()

Python:

cv.cuda.DeviceInfo.canMapHostMemory() -> retval

device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer

clockRate()#

int cv::cuda::DeviceInfo::clockRate()

Python:

cv.cuda.DeviceInfo.clockRate() -> retval

clock frequency in kilohertz

computeMode()#

DeviceInfo::ComputeMode cv::cuda::DeviceInfo::computeMode()

Python:

cv.cuda.DeviceInfo.computeMode() -> retval

compute mode

concurrentKernels()#

bool cv::cuda::DeviceInfo::concurrentKernels()

Python:

cv.cuda.DeviceInfo.concurrentKernels() -> retval

device can possibly execute multiple kernels concurrently

deviceID()#

int cv::cuda::DeviceInfo::deviceID()

Python:

cv.cuda.DeviceInfo.deviceID() -> retval

Returns system index of the CUDA device starting with 0.

ECCEnabled()#

bool cv::cuda::DeviceInfo::ECCEnabled()

Python:

cv.cuda.DeviceInfo.ECCEnabled() -> retval

device has ECC support enabled

freeMemory()#

size_t cv::cuda::DeviceInfo::freeMemory()

Python:

cv.cuda.DeviceInfo.freeMemory() -> retval

integrated()#

bool cv::cuda::DeviceInfo::integrated()

Python:

cv.cuda.DeviceInfo.integrated() -> retval

device is integrated as opposed to discrete

isCompatible()#

bool cv::cuda::DeviceInfo::isCompatible()

Python:

cv.cuda.DeviceInfo.isCompatible() -> retval

Checks the CUDA module and device compatibility.

This function returns true if the CUDA module can be run on the specified device. Otherwise, it returns false .

kernelExecTimeoutEnabled()#

bool cv::cuda::DeviceInfo::kernelExecTimeoutEnabled()

Python:

cv.cuda.DeviceInfo.kernelExecTimeoutEnabled() -> retval

specified whether there is a run time limit on kernels

l2CacheSize()#

int cv::cuda::DeviceInfo::l2CacheSize()

Python:

cv.cuda.DeviceInfo.l2CacheSize() -> retval

size of L2 cache in bytes

majorVersion()#

int cv::cuda::DeviceInfo::majorVersion()

Python:

cv.cuda.DeviceInfo.majorVersion() -> retval

major compute capability

maxGridSize()#

Vec3i cv::cuda::DeviceInfo::maxGridSize()

Python:

cv.cuda.DeviceInfo.maxGridSize() -> retval

maximum size of each dimension of a grid

maxSurface1D()#

int cv::cuda::DeviceInfo::maxSurface1D()

Python:

cv.cuda.DeviceInfo.maxSurface1D() -> retval

maximum 1D surface size

maxSurface1DLayered()#

Vec2i cv::cuda::DeviceInfo::maxSurface1DLayered()

Python:

cv.cuda.DeviceInfo.maxSurface1DLayered() -> retval

maximum 1D layered surface dimensions

maxSurface2D()#

Vec2i cv::cuda::DeviceInfo::maxSurface2D()

Python:

cv.cuda.DeviceInfo.maxSurface2D() -> retval

maximum 2D surface dimensions

maxSurface2DLayered()#

Vec3i cv::cuda::DeviceInfo::maxSurface2DLayered()

Python:

cv.cuda.DeviceInfo.maxSurface2DLayered() -> retval

maximum 2D layered surface dimensions

maxSurface3D()#

Vec3i cv::cuda::DeviceInfo::maxSurface3D()

Python:

cv.cuda.DeviceInfo.maxSurface3D() -> retval

maximum 3D surface dimensions

maxSurfaceCubemap()#

int cv::cuda::DeviceInfo::maxSurfaceCubemap()

Python:

cv.cuda.DeviceInfo.maxSurfaceCubemap() -> retval

maximum Cubemap surface dimensions

maxSurfaceCubemapLayered()#

Vec2i cv::cuda::DeviceInfo::maxSurfaceCubemapLayered()

Python:

cv.cuda.DeviceInfo.maxSurfaceCubemapLayered() -> retval

maximum Cubemap layered surface dimensions

maxTexture1D()#

int cv::cuda::DeviceInfo::maxTexture1D()

Python:

cv.cuda.DeviceInfo.maxTexture1D() -> retval

maximum 1D texture size

maxTexture1DLayered()#

Vec2i cv::cuda::DeviceInfo::maxTexture1DLayered()

Python:

cv.cuda.DeviceInfo.maxTexture1DLayered() -> retval

maximum 1D layered texture dimensions

maxTexture1DLinear()#

int cv::cuda::DeviceInfo::maxTexture1DLinear()

Python:

cv.cuda.DeviceInfo.maxTexture1DLinear() -> retval

maximum size for 1D textures bound to linear memory

maxTexture1DMipmap()#

int cv::cuda::DeviceInfo::maxTexture1DMipmap()

Python:

cv.cuda.DeviceInfo.maxTexture1DMipmap() -> retval

maximum 1D mipmapped texture size

maxTexture2D()#

Vec2i cv::cuda::DeviceInfo::maxTexture2D()

Python:

cv.cuda.DeviceInfo.maxTexture2D() -> retval

maximum 2D texture dimensions

maxTexture2DGather()#

Vec2i cv::cuda::DeviceInfo::maxTexture2DGather()

Python:

cv.cuda.DeviceInfo.maxTexture2DGather() -> retval

maximum 2D texture dimensions if texture gather operations have to be performed

maxTexture2DLayered()#

Vec3i cv::cuda::DeviceInfo::maxTexture2DLayered()

Python:

cv.cuda.DeviceInfo.maxTexture2DLayered() -> retval

maximum 2D layered texture dimensions

maxTexture2DLinear()#

Vec3i cv::cuda::DeviceInfo::maxTexture2DLinear()

Python:

cv.cuda.DeviceInfo.maxTexture2DLinear() -> retval

maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory

maxTexture2DMipmap()#

Vec2i cv::cuda::DeviceInfo::maxTexture2DMipmap()

Python:

cv.cuda.DeviceInfo.maxTexture2DMipmap() -> retval

maximum 2D mipmapped texture dimensions

maxTexture3D()#

Vec3i cv::cuda::DeviceInfo::maxTexture3D()

Python:

cv.cuda.DeviceInfo.maxTexture3D() -> retval

maximum 3D texture dimensions

maxTextureCubemap()#

int cv::cuda::DeviceInfo::maxTextureCubemap()

Python:

cv.cuda.DeviceInfo.maxTextureCubemap() -> retval

maximum Cubemap texture dimensions

maxTextureCubemapLayered()#

Vec2i cv::cuda::DeviceInfo::maxTextureCubemapLayered()

Python:

cv.cuda.DeviceInfo.maxTextureCubemapLayered() -> retval

maximum Cubemap layered texture dimensions

maxThreadsDim()#

Vec3i cv::cuda::DeviceInfo::maxThreadsDim()

Python:

cv.cuda.DeviceInfo.maxThreadsDim() -> retval

maximum size of each dimension of a block

maxThreadsPerBlock()#

int cv::cuda::DeviceInfo::maxThreadsPerBlock()

Python:

cv.cuda.DeviceInfo.maxThreadsPerBlock() -> retval

maximum number of threads per block

maxThreadsPerMultiProcessor()#

int cv::cuda::DeviceInfo::maxThreadsPerMultiProcessor()

Python:

cv.cuda.DeviceInfo.maxThreadsPerMultiProcessor() -> retval

maximum resident threads per multiprocessor

memoryBusWidth()#

int cv::cuda::DeviceInfo::memoryBusWidth()

Python:

cv.cuda.DeviceInfo.memoryBusWidth() -> retval

global memory bus width in bits

memoryClockRate()#

int cv::cuda::DeviceInfo::memoryClockRate()

Python:

cv.cuda.DeviceInfo.memoryClockRate() -> retval

peak memory clock frequency in kilohertz

memPitch()#

size_t cv::cuda::DeviceInfo::memPitch()

Python:

cv.cuda.DeviceInfo.memPitch() -> retval

maximum pitch in bytes allowed by memory copies

minorVersion()#

int cv::cuda::DeviceInfo::minorVersion()

Python:

cv.cuda.DeviceInfo.minorVersion() -> retval

minor compute capability

multiProcessorCount()#

int cv::cuda::DeviceInfo::multiProcessorCount()

Python:

cv.cuda.DeviceInfo.multiProcessorCount() -> retval

number of multiprocessors on device

name()#

const char * cv::cuda::DeviceInfo::name()

ASCII string identifying device.

pciBusID()#

int cv::cuda::DeviceInfo::pciBusID()

Python:

cv.cuda.DeviceInfo.pciBusID() -> retval

PCI bus ID of the device.

pciDeviceID()#

int cv::cuda::DeviceInfo::pciDeviceID()

Python:

cv.cuda.DeviceInfo.pciDeviceID() -> retval

PCI device ID of the device.

pciDomainID()#

int cv::cuda::DeviceInfo::pciDomainID()

Python:

cv.cuda.DeviceInfo.pciDomainID() -> retval

PCI domain ID of the device.

queryMemory()#

void cv::cuda::DeviceInfo::queryMemory(
size_t & totalMemory,
size_t & freeMemory )

Python:

cv.cuda.DeviceInfo.queryMemory(totalMemory, freeMemory)

gets free and total device memory

regsPerBlock()#

int cv::cuda::DeviceInfo::regsPerBlock()

Python:

cv.cuda.DeviceInfo.regsPerBlock() -> retval

32-bit registers available per block

sharedMemPerBlock()#

size_t cv::cuda::DeviceInfo::sharedMemPerBlock()

Python:

cv.cuda.DeviceInfo.sharedMemPerBlock() -> retval

shared memory available per block in bytes

supports()#

bool cv::cuda::DeviceInfo::supports(FeatureSet feature_set)

Provides information on CUDA feature support.

This function returns true if the device has the specified CUDA feature. Otherwise, it returns false

Parameters

feature_set — Features to be checked. See cuda::FeatureSet.

surfaceAlignment()#

size_t cv::cuda::DeviceInfo::surfaceAlignment()

Python:

cv.cuda.DeviceInfo.surfaceAlignment() -> retval

alignment requirements for surfaces

tccDriver()#

bool cv::cuda::DeviceInfo::tccDriver()

Python:

cv.cuda.DeviceInfo.tccDriver() -> retval

true if device is a Tesla device using TCC driver, false otherwise

textureAlignment()#

size_t cv::cuda::DeviceInfo::textureAlignment()

Python:

cv.cuda.DeviceInfo.textureAlignment() -> retval

alignment requirement for textures

texturePitchAlignment()#

size_t cv::cuda::DeviceInfo::texturePitchAlignment()

Python:

cv.cuda.DeviceInfo.texturePitchAlignment() -> retval

pitch alignment requirement for texture references bound to pitched memory

totalConstMem()#

size_t cv::cuda::DeviceInfo::totalConstMem()

Python:

cv.cuda.DeviceInfo.totalConstMem() -> retval

constant memory available on device in bytes

totalGlobalMem()#

size_t cv::cuda::DeviceInfo::totalGlobalMem()

Python:

cv.cuda.DeviceInfo.totalGlobalMem() -> retval

global memory available on device in bytes

totalMemory()#

size_t cv::cuda::DeviceInfo::totalMemory()

Python:

cv.cuda.DeviceInfo.totalMemory() -> retval

unifiedAddressing()#

bool cv::cuda::DeviceInfo::unifiedAddressing()

Python:

cv.cuda.DeviceInfo.unifiedAddressing() -> retval

device shares a unified address space with the host

warpSize()#

int cv::cuda::DeviceInfo::warpSize()

Python:

cv.cuda.DeviceInfo.warpSize() -> retval

warp size in threads

Member Data Documentation#

device_id_#

int cv::cuda::DeviceInfo::device_id_

Source file#

The documentation for this class was generated from the following file:

opencv2/core/cuda.hpp