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| 1 | +package main |
| 2 | + |
| 3 | +import ( |
| 4 | + "fmt" |
| 5 | + "log" |
| 6 | + "math/rand" |
| 7 | + "time" |
| 8 | + |
| 9 | + cuvs "github.com/rapidsai/cuvs/go" |
| 10 | + "github.com/rapidsai/cuvs/go/cagra" |
| 11 | +) |
| 12 | + |
| 13 | +func main() { |
| 14 | + // Initialize resources |
| 15 | + resources, err := cuvs.NewResource(nil) |
| 16 | + if err != nil { |
| 17 | + log.Fatalf("Failed to create resources: %v", err) |
| 18 | + } |
| 19 | + defer resources.Close() |
| 20 | + |
| 21 | + // Dataset |
| 22 | + const ( |
| 23 | + nDatapoints = 65536 |
| 24 | + nFeatures = 512 |
| 25 | + nQueries = 4 |
| 26 | + k = 10 |
| 27 | + ) |
| 28 | + |
| 29 | + // Create random dataset |
| 30 | + rand.Seed(time.Now().UnixNano()) |
| 31 | + dataset := make([][]float32, nDatapoints) |
| 32 | + for i := range dataset { |
| 33 | + dataset[i] = make([]float32, nFeatures) |
| 34 | + for j := range dataset[i] { |
| 35 | + dataset[i][j] = rand.Float32() |
| 36 | + } |
| 37 | + } |
| 38 | + |
| 39 | + // Create tensor from dataset |
| 40 | + datasetTensor, err := cuvs.NewTensor(dataset) |
| 41 | + if err != nil { |
| 42 | + log.Fatalf("Failed to create dataset tensor: %v", err) |
| 43 | + } |
| 44 | + defer datasetTensor.Close() |
| 45 | + |
| 46 | + // Move dataset to GPU |
| 47 | + if _, err := datasetTensor.ToDevice(&resources); err != nil { |
| 48 | + log.Fatalf("Failed to move dataset to GPU: %v", err) |
| 49 | + } |
| 50 | + |
| 51 | + // Create and configure CAGRA index |
| 52 | + indexParams, err := cagra.CreateIndexParams() |
| 53 | + if err != nil { |
| 54 | + log.Fatalf("Failed to create index params: %v", err) |
| 55 | + } |
| 56 | + defer indexParams.Close() |
| 57 | + |
| 58 | + index, err := cagra.CreateIndex() |
| 59 | + if err != nil { |
| 60 | + log.Fatalf("Failed to create index: %v", err) |
| 61 | + } |
| 62 | + defer index.Close() |
| 63 | + |
| 64 | + // Build the index |
| 65 | + fmt.Printf("Building index for %d vectors with %d dimensions...\n", nDatapoints, nFeatures) |
| 66 | + if err := cagra.BuildIndex(resources, indexParams, &datasetTensor, index); err != nil { |
| 67 | + log.Fatalf("Failed to build index: %v", err) |
| 68 | + } |
| 69 | + |
| 70 | + // Create query tensor (using first few vectors as queries) |
| 71 | + queries, err := cuvs.NewTensor(dataset[:nQueries]) |
| 72 | + if err != nil { |
| 73 | + log.Fatalf("Failed to create queries tensor: %v", err) |
| 74 | + } |
| 75 | + defer queries.Close() |
| 76 | + |
| 77 | + // Move queries to GPU |
| 78 | + if _, err := queries.ToDevice(&resources); err != nil { |
| 79 | + log.Fatalf("Failed to move queries to GPU: %v", err) |
| 80 | + } |
| 81 | + |
| 82 | + // Create tensors for results |
| 83 | + neighbors, err := cuvs.NewTensorOnDevice[uint32](&resources, []int64{int64(nQueries), int64(k)}) |
| 84 | + if err != nil { |
| 85 | + log.Fatalf("Failed to create neighbors tensor: %v", err) |
| 86 | + } |
| 87 | + defer neighbors.Close() |
| 88 | + |
| 89 | + distances, err := cuvs.NewTensorOnDevice[float32](&resources, []int64{int64(nQueries), int64(k)}) |
| 90 | + if err != nil { |
| 91 | + log.Fatalf("Failed to create distances tensor: %v", err) |
| 92 | + } |
| 93 | + defer distances.Close() |
| 94 | + |
| 95 | + // Create search parameters |
| 96 | + searchParams, err := cagra.CreateSearchParams() |
| 97 | + if err != nil { |
| 98 | + log.Fatalf("Failed to create search params: %v", err) |
| 99 | + } |
| 100 | + defer searchParams.Close() |
| 101 | + |
| 102 | + // Perform the search |
| 103 | + fmt.Printf("Searching for %d nearest neighbors for %d queries...\n", k, nQueries) |
| 104 | + if err := cagra.SearchIndex(resources, searchParams, index, &queries, &neighbors, &distances, nil); err != nil { |
| 105 | + log.Fatalf("Failed to search index: %v", err) |
| 106 | + } |
| 107 | + |
| 108 | + // Get results |
| 109 | + if _, err := neighbors.ToHost(&resources); err != nil { |
| 110 | + log.Fatalf("Failed to move neighbors to host: %v", err) |
| 111 | + } |
| 112 | + if _, err := distances.ToHost(&resources); err != nil { |
| 113 | + log.Fatalf("Failed to move distances to host: %v", err) |
| 114 | + } |
| 115 | + resources.Sync() |
| 116 | + |
| 117 | + neighborsResult, err := neighbors.Slice() |
| 118 | + if err != nil { |
| 119 | + log.Fatalf("Failed to get neighbors result: %v", err) |
| 120 | + } |
| 121 | + distancesResult, err := distances.Slice() |
| 122 | + if err != nil { |
| 123 | + log.Fatalf("Failed to get distances result: %v", err) |
| 124 | + } |
| 125 | + |
| 126 | + // Print results |
| 127 | + fmt.Println("\nSearch Results:") |
| 128 | + for i := 0; i < nQueries; i++ { |
| 129 | + fmt.Printf("\nQuery %d:\n", i) |
| 130 | + fmt.Printf("Neighbors: %v\n", neighborsResult[i]) |
| 131 | + fmt.Printf("Distances: %v\n", distancesResult[i]) |
| 132 | + } |
| 133 | +} |
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