Integral. Given an input image $pSrc$ and the specified value $nVal$, the pixel value of the integral image $pDst$ at coordinate (i, j) will be computed as. NVIDIA continuously works to improve all of our CUDA libraries. NPP is a particularly large library, with + functions to maintain. We have a realistic goal of. Name, cuda-npp. Version, Summary. Description, CUDA package cuda-npp. Section, base. License, Proprietary. Homepage. Recipe file.
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# (filter “scale_npp” fails to select correct algorithm (Nvidia CUDA/NPP scaler)) – FFmpeg
If an application intends to use NPP with multiple streams then it is the responsibility of the application to call nppSetStream whenever it wishes to change stream IDs. For details please see http: One can see the effect here in a montage of various combinations of hardware and software scalers and encoders. This allows for reuse of the same scratch buffers with any primitive require scratch memory, as long as it is sufficiently sized.
Since NPP is a C API and therefore does not allow for function overloading for different data-types the NPP naming convention addresses the need to differentiate between different flavors of the same algorithm or primitive function but for various data types.
It would be great if you could send us an example of a failure case. To avoid the level of lost information due to clamping most integer primitives allow for result scaling. Last edited 2 years ago by sdack previous diff. All the code in ffmpeg does it passing the interpolation-method on to libnpp. You’ll have to complain to Nvidia about that. If a primitive consumes different type data from what it produces, both types will be listed in the order of consumed to produced data type.
Specially as there is no replacement. Before the results of an operation are clamped to the valid output-data range by multiplying them with. That is that all pointer arguments in those APIs are device pointers. To npp loading and runtime performance when using dynamic libraries, NPP recently replaced it with a full set of nppi sub-libraries.
These allow to specify filter matrices, which I interpret as a sign of quality improvement and a confession on the poor quality of the ResizeSqrPixel? I got maximum speedup in 16 bit Single channel image of size xwhich was When the chda ratio is changed with the size then it behaves as expected again.
One can always undeclare it.
The issue can be observed with CUDA 7. If it turns out to be with Nvidia then who knows when or if this gets fixed.
NVIDIA Performance Primitives | NVIDIA Developer
Because of this fixed-point nature of the representation many numerical operations e. I don’t know yet how this affects the algorithms, but a first test with the shifts changed to 0. Sign up or log in Sign up using Google.
Depending on the host operating system, some additional libraries like pthread or dl might be needed on the linking line.
There are no more identical outputs. It’s then better to give users a “heads up” by declaring it as deprecated, not to make it a secret, and to hope it’s going to change in the np.
For fuda this has the benefit that the library will not allocate memory unbeknownst to the user. Primitives with result scaling have the “Sfs” suffix in their name and provide a parameter “nScaleFactor” that controls the amount of scaling.
Each picture shows the name of the algorithm, an encoder setting and the resulting file size of the video. Scratch-buffer memory is unstructured and may be passed to the primitive in uninitialized form. Primitives belonging to NPP’s image-processing module add cufa letter “i” to the npp prefix, i.
I may have found something. Transfer input data from the host to device using cudaMemCpy The square of which would be clamped to if no result scaling is performed. For best performance the application should first call nppGetStream and only call nppSetStream if the stream ID needs to change, nppSetStream will internally call cudaStreamSynchronize if necessary before changing stream IDs.
Many NPP functions require converting floating-point values to integers.