Notable differences with the single-process, multi-GPU API

The following are a few notable differences between the single-process, multi-GPU cuFFT and cuFFTMp in terms of requirements and API usage.

	Single-process, Multi-GPU	Multi-processes (cuFFTMp)
cufftXtSetGPUs	Required	Not allowed
cufftMpAttachComm	Not allowed	Required
cufftXtMemcpy (...,CUFFT_COPY_HOST_TO_DEVICE)	Copies the entire array from the CPU to multiple GPUs (in natural or permuted order)	Copies the local, distributed array from the CPU to the GPU without redistributing.
cufftXtMemcpy (...,CUFFT_COPY_DEVICE_TO_HOST)	Copies the entire array from multiple GPUs to the CPU (always in natural order)	Copies the local, distributed array from the GPU to the CPU without redistributing.
cufftXtMemcpy (...,CUFFT_COPY_DEVICE_TO_DEVICE)	Redistribute data between GPUs to/from natural order to/from permuted order	Redistribute data between GPUs to/from natural order to/from permuted order (not allowed with cufft XtSetDistribution)
Single-node interconnect	No restrictions	Peer-to-peer required
Descriptor memory	CUDA-visible	NVSHMEM-allocated
cufftXtSetDistribution	Not allowed	Optional
With desc a pointer to a cudaLibXtDesc and nGPUs GPUs	desc->descriptor-> nGPUs == nGPUs	desc->descriptor-> nGPUs == 1
Minimum size (with nGPUs GPUs)	32 in every dimension	nGPUs in the first two dimensions, 2 in the last dimension in 3D.
Maximum number of GPUs	16	No limit
Batched transforms	Supported (but individual batches are not distributed across GPUs)	Not supported