diff --git a/MicroBenchmarks/LoopVectorization/CMakeLists.txt b/MicroBenchmarks/LoopVectorization/CMakeLists.txt
index 516cafbe6141..da4555b967e6 100644
--- a/MicroBenchmarks/LoopVectorization/CMakeLists.txt
+++ b/MicroBenchmarks/LoopVectorization/CMakeLists.txt
@@ -11,6 +11,7 @@ llvm_test_run()
 
 llvm_test_executable(LoopVectorizationBenchmarks
   ConditionalScalarAssignment.cpp
+  Histograms.cpp
   main.cpp
   MathFunctions.cpp
   RuntimeChecks.cpp
diff --git a/MicroBenchmarks/LoopVectorization/Histograms.cpp b/MicroBenchmarks/LoopVectorization/Histograms.cpp
new file mode 100644
index 000000000000..d01d7cb84146
--- /dev/null
+++ b/MicroBenchmarks/LoopVectorization/Histograms.cpp
@@ -0,0 +1,166 @@
+#include <cstring>
+#include <iostream>
+#include <memory>
+#include <random>
+
+#include "benchmark/benchmark.h"
+
+#define ITERATIONS 100000
+#define BUCKETS 10000
+
+template <typename IdxT, typename DataT>
+using HistFn = DataT (*)(IdxT *, DataT * __restrict, DataT * __restrict);
+
+#define INIT_BLOCK
+#define EXIT_BLOCK
+
+#define _Args(...) __VA_ARGS__
+#define _STRIP_PARENS(X) X
+#define STRIP_PARENS(X) _STRIP_PARENS(_Args X)
+
+#define DEF_HIST_LOOP_FN(name, init, loop, result)                             \
+  template <typename IdxT, typename DataT>                                     \
+  __attribute__((noinline)) static DataT                                       \
+run_##name##_autovec(IdxT *A, DataT * __restrict B, DataT * __restrict C) {    \
+    STRIP_PARENS(init);                                                        \
+    STRIP_PARENS(loop);                                                        \
+    result;                                                                    \
+  }                                                                            \
+  template <typename IdxT, typename DataT>                                     \
+  __attribute__((noinline)) static DataT                                       \
+run_##name##_novec(IdxT *A, DataT * __restrict B, DataT * __restrict C) {      \
+    STRIP_PARENS(init);                                                        \
+    _Pragma("clang loop vectorize(disable) interleave(disable)")               \
+        STRIP_PARENS(loop);                                                    \
+    result;                                                                    \
+  }
+
+#define DEF_HIST_LOOP(name, loop)                                              \
+  DEF_HIST_LOOP_FN(name,                                                       \
+               (DataT Result{};),                                              \
+               loop, ({ return Result; }));
+
+// Compute the histogram of values in A using buckets in B
+DEF_HIST_LOOP(single_hist_only,
+                    (for (unsigned i = 0; i < ITERATIONS; i++) {
+                      B[A[i]]++;
+                    } Result = B[0];));
+
+// Compute the histogram of values in A using buckets in B and C
+DEF_HIST_LOOP(multi_hist_only,
+                    (for (unsigned i = 0; i < ITERATIONS; i++) {
+                      B[A[i]]++;
+                      C[A[i]]++;
+                    } Result = C[0];));
+
+// Compute the histogram of values in A using buckets in B, along with some
+// extra arithmetic
+DEF_HIST_LOOP(single_hist_with_arith,
+                    (for (unsigned i = 0; i < ITERATIONS; i++) {
+                      B[A[i]]++;
+                      Result += DataT(A[i]) * 3 + 17;
+                    }));
+
+// Initialize array A with random numbers within the range of available buckets.
+template <typename T> static void init_data(T *A) {
+  std::uniform_int_distribution<T> dist(0, BUCKETS - 1);
+  std::mt19937 rng(12345);
+  for (unsigned i = 0; i < ITERATIONS; i++)
+    A[i] = dist(rng);
+}
+
+// Benchmark auto-vectorized version.
+template <typename IdxT, typename DataT>
+static void __attribute__((always_inline))
+bench_hist_autovec(benchmark::State &state, HistFn<IdxT, DataT> VecFn,
+                   HistFn<IdxT, DataT> NoVecFn) {
+  std::unique_ptr<IdxT[]> A(new IdxT[ITERATIONS]);
+  std::unique_ptr<DataT[]> B(new DataT[BUCKETS]);
+  std::unique_ptr<DataT[]> C(new DataT[BUCKETS]);
+  init_data(&A[0]);
+  std::memset(&B[0], 0, BUCKETS * sizeof(DataT));
+  std::memset(&C[0], 0, BUCKETS * sizeof(DataT));
+
+#ifdef BENCH_AND_VERIFY
+  std::unique_ptr<DataT[]> BNoVec(new DataT[BUCKETS]);
+  std::unique_ptr<DataT[]> CNoVec(new DataT[BUCKETS]);
+  std::memset(&BNoVec[0], 0, BUCKETS * sizeof(DataT));
+  std::memset(&CNoVec[0], 0, BUCKETS * sizeof(DataT));
+  // Verify the vectorized and un-vectorized versions produce the same results.
+  {
+    DataT VecRes = VecFn(&A[0], &B[0], &C[0]);
+    DataT NoVecRes = NoVecFn(&A[0], &BNoVec[0], &CNoVec[0]);
+    if (VecRes != NoVecRes) {
+      std::cerr << "ERROR: autovec result different to scalar result " <<
+                   VecRes << " != " << NoVecRes << "\n";
+      exit(1);
+    }
+    for (unsigned i = 0; i < BUCKETS; i++) {
+      if (B[i] != BNoVec[i]) {
+        std::cerr << "ERROR: autovec B array different to scalar " << B[i]
+                  << " != " << BNoVec[i] << " at index " << i << "\n";
+        exit(1);
+      }
+      if (C[i] != CNoVec[i]) {
+        std::cerr << "ERROR: autovec C array different to scalar " << C[i]
+                  << " != " << CNoVec[i] << " at index " << i << "\n";
+        exit(1);
+      }
+    }
+  }
+#endif
+
+  for (auto _ : state) {
+    VecFn(&A[0], &B[0], &C[0]);
+    benchmark::DoNotOptimize(A);
+    benchmark::DoNotOptimize(B);
+    benchmark::DoNotOptimize(C);
+    benchmark::ClobberMemory();
+  }
+}
+
+// Benchmark version with vectorization disabled.
+template <typename IdxT, typename DataT>
+static void __attribute__((always_inline))
+bench_hist_novec(benchmark::State &state, HistFn<IdxT, DataT> NoVecFn) {
+  std::unique_ptr<IdxT[]> A(new IdxT[ITERATIONS]);
+  std::unique_ptr<DataT[]> B(new DataT[BUCKETS]);
+  std::unique_ptr<DataT[]> C(new DataT[BUCKETS]);
+  init_data(&A[0]);
+  std::memset(&B[0], 0, BUCKETS * sizeof(DataT));
+  std::memset(&C[0], 0, BUCKETS * sizeof(DataT));
+
+  for (auto _ : state) {
+    NoVecFn(&A[0], &B[0], &C[0]);
+    benchmark::DoNotOptimize(A);
+    benchmark::DoNotOptimize(B);
+    benchmark::DoNotOptimize(C);
+    benchmark::ClobberMemory();
+  }
+}
+
+#define BENCHMARK_CASE(name, IdxT, DataT)                                      \
+  void BENCHMARK_##name##_autovec_##IdxT##_##DataT##_(benchmark::State &state){\
+    bench_hist_autovec<IdxT, DataT>(state, run_##name##_autovec,               \
+                                    run_##name##_novec);                       \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_##name##_autovec_##IdxT##_##DataT##_)->Unit(             \
+                                                      benchmark::kNanosecond); \
+                                                                               \
+  void BENCHMARK_##name##_novec_##IdxT##_##DataT##_(benchmark::State &state) { \
+    bench_hist_novec<IdxT, DataT>(state, run_##name##_novec);                  \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_##name##_novec_##IdxT##_##DataT##_)->Unit(               \
+                                                        benchmark::kNanosecond);
+
+
+#define ADD_BENCHMARK(IdxT, DataT)                                             \
+  BENCHMARK_CASE(single_hist_only, IdxT, DataT)                                \
+  BENCHMARK_CASE(multi_hist_only, IdxT, DataT)                                 \
+  BENCHMARK_CASE(single_hist_with_arith, IdxT, DataT)
+
+ADD_BENCHMARK(uint8_t, uint8_t)
+ADD_BENCHMARK(uint32_t, uint8_t)
+ADD_BENCHMARK(uint32_t, uint16_t)
+ADD_BENCHMARK(uint32_t, int32_t)
+ADD_BENCHMARK(int64_t, int64_t)