Initial commit

packages/leann-backend-hnsw/third_party/faiss/tutorial/cpp/4-GPU.cpp

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+/*
+ * Copyright (c) Meta Platforms, Inc. and affiliates.
+ *
+ * This source code is licensed under the MIT license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+#include <cassert>
+#include <cstdio>
+#include <cstdlib>
+#include <random>
+
+#include <faiss/IndexFlat.h>
+#include <faiss/gpu/GpuIndexFlat.h>
+#include <faiss/gpu/GpuIndexIVFFlat.h>
+#include <faiss/gpu/StandardGpuResources.h>
+
+int main() {
+    int d = 64;      // dimension
+    int nb = 100000; // database size
+    int nq = 10000;  // nb of queries
+
+    std::mt19937 rng;
+    std::uniform_real_distribution<> distrib;
+
+    float* xb = new float[d * nb];
+    float* xq = new float[d * nq];
+
+    for (int i = 0; i < nb; i++) {
+        for (int j = 0; j < d; j++)
+            xb[d * i + j] = distrib(rng);
+        xb[d * i] += i / 1000.;
+    }
+
+    for (int i = 0; i < nq; i++) {
+        for (int j = 0; j < d; j++)
+            xq[d * i + j] = distrib(rng);
+        xq[d * i] += i / 1000.;
+    }
+
+    faiss::gpu::StandardGpuResources res;
+
+    // Using a flat index
+
+    faiss::gpu::GpuIndexFlatL2 index_flat(&res, d);
+
+    printf("is_trained = %s\n", index_flat.is_trained ? "true" : "false");
+    index_flat.add(nb, xb); // add vectors to the index
+    printf("ntotal = %ld\n", index_flat.ntotal);
+
+    int k = 4;
+
+    { // search xq
+        long* I = new long[k * nq];
+        float* D = new float[k * nq];
+
+        index_flat.search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("I (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    // Using an IVF index
+
+    int nlist = 100;
+    faiss::gpu::GpuIndexIVFFlat index_ivf(&res, d, nlist, faiss::METRIC_L2);
+
+    assert(!index_ivf.is_trained);
+    index_ivf.train(nb, xb);
+    assert(index_ivf.is_trained);
+    index_ivf.add(nb, xb); // add vectors to the index
+
+    printf("is_trained = %s\n", index_ivf.is_trained ? "true" : "false");
+    printf("ntotal = %ld\n", index_ivf.ntotal);
+
+    { // search xq
+        long* I = new long[k * nq];
+        float* D = new float[k * nq];
+
+        index_ivf.search(nq, xq, k, D, I);
+
+        // print results
+        printf("I (5 first results)=\n");
+        for (int i = 0; i < 5; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        printf("I (5 last results)=\n");
+        for (int i = nq - 5; i < nq; i++) {
+            for (int j = 0; j < k; j++)
+                printf("%5ld ", I[i * k + j]);
+            printf("\n");
+        }
+
+        delete[] I;
+        delete[] D;
+    }
+
+    delete[] xb;
+    delete[] xq;
+
+    return 0;
+}