| %*%.cudatensor | Arithmetic operators for GPU-aware tensors |
| as_adjacency_matrix | Extract a graph adjacency matrix |
| as_coo | Convert sparse storage format |
| as_csr | Convert sparse storage format |
| cudatensor-operators | Arithmetic operators for GPU-aware tensors |
| cudatensor-subset | Subset and replace tensor values |
| cuda_available | Detect a usable CUDA backend |
| cuda_diagnostics | Diagnose the optional CUDA runtime |
| cuda_diffusion_map | Diffusion-map-style embedding |
| cuda_distance | Pairwise distances with an optional CUDA backend |
| cuda_kmeans | GPU-aware k-means clustering |
| cuda_knn | k-nearest neighbours |
| cuda_knn_graph | Build a sparse graph from nearest neighbours |
| cuda_leiden | Cluster a graph with Leiden |
| cuda_louvain | Cluster a graph with Louvain |
| cuda_memory_info | Inspect CUDA memory |
| cuda_pca | GPU-aware principal component analysis |
| cuda_provenance | Inspect actual compute provenance |
| cuda_provenance.default | Inspect actual compute provenance |
| cuda_select_device | Select a computation device without hiding fallback |
| cuda_sparse | Create a GPU-aware sparse matrix |
| cuda_stage | Record one compute stage |
| cuda_svd | GPU-aware singular value decomposition |
| cuda_tensor | Create a GPU-aware tensor |
| cuda_tsne | t-SNE embedding |
| cuda_umap | UMAP embedding |
| dimnames.cudasparse | Inspect sparse matrix dimension labels |
| dimnames.cudatensor | Inspect tensor dimension labels |
| embedding_coordinates | Extract embedding coordinates |
| Ops.cudatensor | Arithmetic operators for GPU-aware tensors |
| predict.cuda_kmeans | Assign observations with a fitted CUDA-aware k-means model |
| predict.cuda_pca | Project observations with a fitted CUDA-aware PCA model |
| sparse_col_sums | Sparse row and column reductions |
| sparse_info | Inspect sparse matrix metadata |
| sparse_matmul_dense | Sparse matrix by dense matrix multiplication |
| sparse_matvec | Sparse matrix-vector multiplication |
| sparse_normalize | Normalize sparse rows or columns without densifying |
| sparse_row_sums | Sparse row and column reductions |
| t.cudasparse | Transpose a GPU-aware sparse matrix |
| tensor_broadcast_to | Broadcast a tensor to a compatible shape |
| tensor_device | Inspect tensor device and backend |
| tensor_matmul | Matrix multiplication for tensors |
| tensor_mean | Tensor reductions |
| tensor_reshape | Reshape a tensor without changing its values |
| tensor_shape | Inspect tensor shape |
| tensor_sum | Tensor reductions |
| to_cpu | Transfer tensor data to base R |
| to_device | Transfer a tensor to a device |
| to_dgCMatrix | Convert to an R sparse matrix |
| [.cudatensor | Subset and replace tensor values |
| [<-.cudatensor | Subset and replace tensor values |