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> For full documentation content, see https://docs.nvidia.com/cuvs/llms-full.txt.
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# Common Types

Use these guides to understand the shared resource, memory, and array abstractions used by NVIDIA cuVS APIs.

- [Array Types](/user-guide/api-guides/core-types/array-types): choose between dense arrays and sparse arrays for NVIDIA cuVS APIs.
- [Dense Arrays](/user-guide/api-guides/core-types/array-types/dense-arrays): pass dense vectors, matrices, and outputs into NVIDIA cuVS APIs across supported languages.
- [Memory Management](/user-guide/api-guides/core-types/memory-management): configure RMM device, pool, pinned host, host, and managed memory resources for NVIDIA cuVS workflows.
- [Multi-GPU](/user-guide/api-guides/core-types/multi-gpu): initialize multi-GPU resources and understand RAFT/NCCL communication setup.
- [Resources](/user-guide/api-guides/core-types/resources): reuse CUDA streams, library handles, stream pools, and workspace resources across NVIDIA cuVS calls.
- [Sparse Arrays](/user-guide/api-guides/core-types/array-types/sparse-arrays): use CSR and COO sparse matrix views with NVIDIA cuVS C++ APIs that accept sparse inputs.