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Cuda Driver Api


If CU_MEM_ADVISE_SET_READ_MOSTLY is also set on this memory region or any subset of it, then the policies associated with that advice will override the policies of this advice. CU_CTX_MAP_HOST: Instruct CUDA to support mapped pinned allocations. Synchronous All transfers involving Unified Memory regions are fully synchronous with respect to the host. CU_MEM_ADVISE_UNSET_READ_MOSTLY: Undoes the effect of CU_MEM_ADVISE_SET_READ_MOSTLY and also prevents the Unified Memory driver from attempting heuristic read-duplication on the memory range. http://mdportal.net/cuda-driver/cuda-drivers.html

Is this Threading and Swing behaviour a bug or intended? In the reference documentation, each memcpy function is categorized as synchronous or asynchronous, corresponding to the definitions below. asked 3 years, 9 months ago viewed 721 times active 1 year, 3 months ago Blog New Kids on the Block: Understanding Developers Entering the Workforce Today Related 32CUDA Driver API pCudaDevices - Returned CUDA devices. http://docs.nvidia.com/cuda/cuda-driver-api/

Cuda Driver Api Example

Automatic Registration of Peer Memory Upon enabling direct access from a context that supports unified addressing to another peer context that supports unified addressing using cuCtxEnablePeerAccess() all memory allocated in the If CU_MEM_ADVISE_SET_ACCESSED_BY was called on any subset of this memory range, then mappings to those pages from all the appropriate processors are updated to refer to the new location if establishing The function cuMemcpy() may be used to perform a copy between two pointers, ignoring whether they point to host or device memory (making cuMemcpyHtoD(), cuMemcpyDtoD(), and cuMemcpyDtoH() unnecessary for devices supporting Note that for most allocations in the unified virtual address space the host and device pointer for accessing the allocation will be the same.

This is a misnomer as each function may exhibit synchronous or asynchronous behavior depending on the arguments passed to the function. CU_LIMIT_PRINTF_FIFO_SIZE controls the size in bytes of the FIFO used by the printf() device system call. If any of the GPUs being used by the current OpenGL context are not CUDA capable then the call will return CUDA_ERROR_NO_DEVICE. Cudeviceprimaryctxretain The programmer has to directly deal with initialization, module loading, etc.

This can prevent thrashing by local memory allocations when launching many kernels with high local memory usage at the cost of potentially increased memory usage. These APIs are mutually exclusive: An application should use either one or the other. In principle nothing. http://docs.nvidia.com/cuda/cuda-driver-api/group__CUDA__CTX__DEPRECATED.html Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the data located on one GPU is occasionally accessed by peer GPUs.

The memory range must refer to managed memory allocated via cuMemAllocManaged or declared via __managed__ variables. Cuctxcreate The driver is free to modify the requested value to meet h/w requirements (this could be clamping to minimum or maximum values, rounding up to nearest element size, etc). Note:Note that this function may also return error codes from previous, asynchronous launches. CU_POINTER_ATTRIBUTE_IS_MANAGED: Returns in *data a boolean that indicates whether the pointer points to managed memory or not.

Cuda Runtime Api

Hot Network Questions When I lose concentration while levitating, do I fall? It also comes closer to cudaSetDevice(), except that it takes a context as argument and not the deviceID, and doesn't create a new context on first call. –kunzmi Aug 19 '13 Cuda Driver Api Example See also: cuCtxCreate, cuCtxDestroy, cuCtxGetApiVersion, cuCtxGetDevice, cuCtxGetFlags, cuCtxGetLimit, cuCtxPopCurrent, cuCtxPushCurrent, cuCtxSetCacheConfig, cuCtxSetLimit, cuCtxSynchronize, cuFuncSetCacheConfig CUresult cuCtxGetCurrent ( CUcontext*pctx ) Returns the CUDA context bound to the calling CPU thread. Cuda Driver Api Vs Runtime Api Passing in CU_DEVICE_CPU for dstDevice will prefetch the data to host memory.

CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED: Device supports Compute Preemption. check over here The nvidia-smi tool can be used to set the compute mode for * devices. If any page in the memory range was never explicitly prefetched or if all pages were not prefetched to the same location, CU_DEVICE_INVALID will be returned. Also cfr. Cumoduleload

Note:Note that this function may also return error codes from previous, asynchronous launches. CU_GRAPHICS_REGISTER_FLAGS_TEXTURE_GATHER: Specifies that CUDA will perform texture gather operations on this resource. Just wondering if there is an equivalent call in the driver API. his comment is here Note:Note that this function may also return error codes from previous, asynchronous launches.

This is only a preference. Cumoduleloaddataex Also, device emulation (see Section does not work with the CUDA driver API. If any processor writes to this region, all copies of the corresponding page will be invalidated except for the one where the write occurred.

Supported Platforms Whether or not a device supports unified addressing may be queried by calling cuDeviceGetAttribute() with the device attribute CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING.

This function exhibits asynchronous behavior for most use cases. Keep in mind that being able to sustain additional pending launches will require the driver to reserve larger amounts of device memory upfront which can no longer be used for allocations. Having a preferred location can override the page thrash detection and resolution logic in the Unified Memory driver. Culaunchkernel If there exists no host pointer value through which the host program may directly access ptr then CUDA_ERROR_INVALID_VALUE is returned.

CU_DEVICE_ATTRIBUTE_HOST_NATIVE_ATOMIC_SUPPORTED: 1 if Link between the device and the host supports native atomic operations. oh and currently cudpp which is a very handy library only works with the runtime api. CU_CTX_LMEM_RESIZE_TO_MAX: Instruct CUDA to not reduce local memory after resizing local memory for a kernel. weblink Instead it's as I posted: One creates a handle to a device and creates a context (implicitly setting the device).

J share|improve this answer answered Mar 25 '10 at 22:48 Jason Dale 15112 1 Can you elaborate more, or link to somewhere, explaining how using the driver directly helps you See also: cuCtxCreate, cuCtxDestroy, cuCtxGetApiVersion, cuCtxGetCacheConfig, cuCtxGetDevice, cuCtxGetFlags, cuCtxGetLimit, cuCtxPopCurrent, cuCtxSetCacheConfig, cuCtxSetLimit, cuCtxSynchronize CUresult cuCtxSetCacheConfig ( CUfunc_cacheconfig ) Sets the preferred cache configuration for the current context. Parameters value - Pointer to memory containing the value to be set attribute - Pointer attribute to set ptr - Pointer to a memory region allocated using CUDA memory allocation APIs This is the default value.

Not the answer you're looking for? If ptr was not allocated by, mapped by, or registered with a CUcontext which uses unified virtual addressing then CUDA_ERROR_INVALID_VALUE is returned. Comic book short story where a couple of robots take off their metal skin and get eaten by bugs How can we handle "firing" our DM? See also: cuPointerSetAttribute, cuMemAlloc, cuMemFree, cuMemAllocHost, cuMemFreeHost, cuMemHostAlloc, cuMemHostRegister, cuMemHostUnregister CUresult cuPointerGetAttributes ( unsigned int numAttributes, CUpointer_attribute*attributes, void**data, CUdeviceptrptr ) Returns information about a pointer.

Note:Note that this function may also return error codes from previous, asynchronous launches. CUresultcuMemRangeGetAttribute ( void*data, size_tdataSize, CUmem_range_attributeattribute, CUdeviceptrdevPtr, size_tcount ) Query an attribute of a given memory range. NVIDIACUDA Toolkit Documentation Search In:Entire SiteJust This Documentclear searchsearch CUDA Toolkit v8.0 CUDA Driver API 1.Difference between the driver and runtime APIs 2.API synchronization behavior 3.Stream synchronization behavior 4.Modules 4.1.Data types target must match the type of the object, and must be one of GL_TEXTURE_2D, GL_TEXTURE_RECTANGLE, GL_TEXTURE_CUBE_MAP, GL_TEXTURE_3D, GL_TEXTURE_2D_ARRAY, or GL_RENDERBUFFER.

The function cuDeviceGetAttribute() can be used with CU_DEVICE_ATTRIBUTE_COMPUTE_MODE to determine the compute mode of the device. CU_LIMIT_MALLOC_HEAP_SIZE: size in bytes of the heap used by the malloc() and free() device system calls. As another example, in the case of device memory, one may want to know on which CUDA device the memory resides. The location for the collapsed copy will be the preferred location if the page has a preferred location and one of the read-duplicated copies was resident at that location.

Note:Note that this function may also return error codes from previous, asynchronous launches. Parameters pconfig - Returned cache configuration Returns CUDA_SUCCESS, CUDA_ERROR_DEINITIALIZED, CUDA_ERROR_NOT_INITIALIZED, CUDA_ERROR_INVALID_CONTEXT, CUDA_ERROR_INVALID_VALUE Description On devices where the L1 cache and shared memory use the same hardware resources, this function returns through