diff --git a/internal/ceres/single_linkage_clustering.cc b/internal/ceres/single_linkage_clustering.cc
new file mode 100644
index 0000000..54b4379
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+++ b/internal/ceres/single_linkage_clustering.cc
@@ -0,0 +1,107 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2013 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// * Redistributions of source code must retain the above copyright notice,
+//   this list of conditions and the following disclaimer.
+// * Redistributions in binary form must reproduce the above copyright notice,
+//   this list of conditions and the following disclaimer in the documentation
+//   and/or other materials provided with the distribution.
+// * Neither the name of Google Inc. nor the names of its contributors may be
+//   used to endorse or promote products derived from this software without
+//   specific prior written permission.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+// POSSIBILITY OF SUCH DAMAGE.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_NO_SUITESPARSE
+
+#include "ceres/single_linkage_clustering.h"
+
+#include "ceres/graph.h"
+#include "ceres/collections_port.h"
+#include "ceres/graph_algorithms.h"
+
+namespace ceres {
+namespace internal {
+
+int ComputeSingleLinkageClustering(
+    const SingleLinkageClusteringOptions& options,
+    const Graph<int>& graph,
+    HashMap<int, int>* membership) {
+  CHECK_NOTNULL(membership)->clear();
+
+  // Initially each vertex is in its own cluster.
+  const HashSet<int>& vertices = graph.vertices();
+  for (HashSet<int>::const_iterator it = vertices.begin();
+       it != vertices.end();
+       ++it) {
+    (*membership)[*it] = *it;
+  }
+
+  for (HashSet<int>::const_iterator it1 = vertices.begin();
+       it1 != vertices.end();
+       ++it1) {
+    const int vertex1 = *it1;
+    const HashSet<int>& neighbors = graph.Neighbors(vertex1);
+    for (HashSet<int>::const_iterator it2 = neighbors.begin();
+         it2 != neighbors.end();
+         ++it2) {
+      const int vertex2 = *it2;
+
+      // Since the graph is undirected, only pay attention to one side
+      // of the edge and ignore weak edges.
+      if ((vertex1 > vertex2) ||
+          (graph.EdgeWeight(vertex1, vertex2) < options.min_similarity)) {
+        continue;
+      }
+
+      // Use a union-find algorithm to keep track of the clusters.
+      const int c1 = FindConnectedComponent(vertex1, membership);
+      const int c2 = FindConnectedComponent(vertex2, membership);
+
+      if (c1 == c2) {
+        continue;
+      }
+
+      if (c1 < c2) {
+        (*membership)[c2] = c1;
+      } else {
+        (*membership)[c1] = c2;
+      }
+    }
+  }
+
+  // Make sure that every vertex is connected directly to the vertex
+  // identifying the cluster.
+  int num_clusters = 0;
+  for (HashMap<int, int>::iterator it = membership->begin();
+       it != membership->end();
+       ++it) {
+    it->second = FindConnectedComponent(it->first, membership);
+    if (it->first == it->second) {
+      ++num_clusters;
+    }
+  }
+
+  return num_clusters;
+}
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_NO_SUITESPARSE