diff --git a/MicroBenchmarks/LoopVectorization/CMakeLists.txt b/MicroBenchmarks/LoopVectorization/CMakeLists.txt
index 03e84ad800..6d5f0c7019 100644
--- a/MicroBenchmarks/LoopVectorization/CMakeLists.txt
+++ b/MicroBenchmarks/LoopVectorization/CMakeLists.txt
@@ -10,6 +10,7 @@ endif()
 llvm_test_run()
 
 llvm_test_executable(LoopVectorizationBenchmarks
+  ConditionalScalarAssignment.cpp
   main.cpp
   MathFunctions.cpp
   RuntimeChecks.cpp
diff --git a/MicroBenchmarks/LoopVectorization/ConditionalScalarAssignment.cpp b/MicroBenchmarks/LoopVectorization/ConditionalScalarAssignment.cpp
new file mode 100644
index 0000000000..9470465855
--- /dev/null
+++ b/MicroBenchmarks/LoopVectorization/ConditionalScalarAssignment.cpp
@@ -0,0 +1,222 @@
+#include <iostream>
+#include <memory>
+#include <random>
+
+#include "benchmark/benchmark.h"
+
+#define ITERATIONS 100000
+
+template <typename T>
+using CSAFunc = T (*)(T *, T *, T *, T);
+
+// Find the last element in A above the given threshold,
+// with default loop vectorization settings.
+template <typename T>
+static T run_single_csa_only_autovec(T *A, T *B, T *C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A' in init_data below.
+  T Result = 101;
+  for (unsigned i = 0; i < ITERATIONS; i++)
+    if (A[i] > Threshold)
+      Result = A[i];
+
+  return Result;
+}
+
+// Find the last element in A above the given threshold,
+// with loop vectorization disabled.
+template <typename T>
+static T run_single_csa_only_novec(T *A, T *B, T *C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A' in init_data below.
+  T Result = 101;
+#pragma clang loop vectorize(disable) interleave(disable)
+  for (unsigned i = 0; i < ITERATIONS; i++)
+    if (A[i] > Threshold)
+      Result = A[i];
+
+  return Result;
+}
+
+// Find the last elements in A, B, and C above the given threshold,
+// with default loop vectorization settings.
+template <typename T>
+static T run_multi_csa_only_autovec(T *A, T *B, T *C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A', 'B', and 'C' in init_data below.
+  T ResultA = 101;
+  T ResultB = 101;
+  T ResultC = 101;
+  for (unsigned i = 0; i < ITERATIONS; i++) {
+    if (A[i] > Threshold)
+      ResultA = A[i];
+    if (B[i] > Threshold)
+      ResultB = B[i];
+    if (C[i] > Threshold)
+      ResultC = C[i];
+  }
+
+  return ResultA ^ ResultB ^ ResultC;
+}
+
+// Find the last elements in A, B, and C above the given threshold,
+// with loop vectorization disabled.
+template <typename T>
+static T run_multi_csa_only_novec(T *A, T *B, T *C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A', 'B', and 'C' in init_data below.
+  T ResultA = 101;
+  T ResultB = 101;
+  T ResultC = 101;
+#pragma clang loop vectorize(disable) interleave(disable)
+  for (unsigned i = 0; i < ITERATIONS; i++) {
+    if (A[i] > Threshold)
+      ResultA = A[i];
+    if (B[i] > Threshold)
+      ResultB = B[i];
+    if (C[i] > Threshold)
+      ResultC = C[i];
+  }
+
+  return ResultA ^ ResultB ^ ResultC;
+}
+
+// Find the last element in A above the given threshold,
+// with default loop vectorization settings.
+template <typename T>
+static T run_csa_with_arith_autovec(T *A, T *B, T *C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A' in init_data below.
+  T Result = 101;
+  for (unsigned i = 0; i < ITERATIONS; i++) {
+    // Do some work to make the difference noticeable
+    C[i] = A[i] * 13 + B[i] * 5;
+    if (A[i] > Threshold)
+      Result = A[i];
+  }
+
+  return Result;
+}
+
+// Find the last element in A above the given threshold,
+// with loop vectorization disabled.
+template <typename T>
+static T run_csa_with_arith_novec(T *A, T *B, T* C, T Threshold) {
+  // Pick a default value that's out of range of the uniform distribution
+  // created for 'A' in init_data below.
+  T Result = 101;
+#pragma clang loop vectorize(disable) interleave(disable)
+  for (unsigned i = 0; i < ITERATIONS; i++) {
+    // Do some work to make the difference noticeable
+    C[i] = A[i] * 13 + B[i] * 5;
+    if (A[i] > Threshold)
+      Result = A[i];
+  }
+
+  return Result;
+}
+
+// Initialize arrays A, B, and C with random numbers
+template <typename T> static void init_data(T *A, T* B, T *C) {
+  std::uniform_int_distribution<T> dist(0, 100);
+  std::mt19937 rng(12345);
+  for (unsigned i = 0; i < ITERATIONS; i++) {
+    A[i] = dist(rng);
+    B[i] = dist(rng);
+    C[i] = dist(rng);
+  }
+}
+
+// Benchmark auto-vectorized version.
+template <typename T>
+static void __attribute__((always_inline))
+benchmark_csa_autovec(benchmark::State &state, CSAFunc<T> VecFn,
+                      CSAFunc<T> NoVecFn, T Threshold) {
+  std::unique_ptr<T[]> A(new T[ITERATIONS]);
+  std::unique_ptr<T[]> B(new T[ITERATIONS]);
+  std::unique_ptr<T[]> C(new T[ITERATIONS]);
+  init_data(&A[0], &B[0], &C[0]);
+
+#ifdef BENCH_AND_VERIFY
+  // Verify the vectorized and un-vectorized versions produce the same results.
+  {
+    T VecRes = VecFn(&A[0], &B[0], &C[0], Threshold);
+    T NoVecRes = NoVecFn(&A[0], &B[0], &C[0], Threshold);
+    // We're only interested in whether the conditional assignment results
+    // were the same.
+    if (VecRes != NoVecRes) {
+      std::cerr << "ERROR: autovec result different to scalar result; "
+                << VecRes << " != " << NoVecRes << "\n";
+      exit(1);
+    }
+  }
+#endif
+
+  for (auto _ : state) {
+    VecFn(&A[0], &B[0], &C[0], Threshold);
+    benchmark::DoNotOptimize(A);
+    benchmark::DoNotOptimize(B);
+    benchmark::DoNotOptimize(C);
+    benchmark::ClobberMemory();
+  }
+}
+
+// Benchmark version with vectorization disabled.
+template <typename T>
+static void __attribute__((always_inline))
+benchmark_csa_novec(benchmark::State &state, CSAFunc<T> NoVecFn, T Threshold) {
+  std::unique_ptr<T[]> A(new T[ITERATIONS]);
+  std::unique_ptr<T[]> B(new T[ITERATIONS]);
+  std::unique_ptr<T[]> C(new T[ITERATIONS]);
+  init_data(&A[0], &B[0], &C[0]);
+
+  for (auto _ : state) {
+    NoVecFn(&A[0], &B[0], &C[0], Threshold);
+    benchmark::DoNotOptimize(A);
+    benchmark::DoNotOptimize(B);
+    benchmark::DoNotOptimize(C);
+  }
+}
+
+// Add benchmarks with and without auto-vectorization
+#define ADD_BENCHMARK(ty, Threshold)                                           \
+  void BENCHMARK_single_csa_only_autovec_##ty##_(benchmark::State &state) {    \
+    benchmark_csa_autovec<ty>(state, run_single_csa_only_autovec,              \
+                              run_single_csa_only_novec, Threshold);           \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_single_csa_only_autovec_##ty##_)->Unit(                  \
+                                                      benchmark::kNanosecond); \
+                                                                               \
+  void BENCHMARK_single_csa_only_novec_##ty##_(benchmark::State &state) {      \
+    benchmark_csa_novec<ty>(state, run_single_csa_only_novec, Threshold);      \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_single_csa_only_novec_##ty##_)->Unit(                    \
+                                                      benchmark::kNanosecond); \
+  void BENCHMARK_multi_csa_only_autovec_##ty##_(benchmark::State &state) {     \
+    benchmark_csa_autovec<ty>(state, run_multi_csa_only_autovec,               \
+                              run_multi_csa_only_novec, Threshold);            \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_multi_csa_only_autovec_##ty##_)->Unit(                   \
+                                                      benchmark::kNanosecond); \
+                                                                               \
+  void BENCHMARK_multi_csa_only_novec_##ty##_(benchmark::State &state) {       \
+    benchmark_csa_novec<ty>(state, run_multi_csa_only_novec, Threshold);       \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_multi_csa_only_novec_##ty##_)->Unit(                     \
+                                                      benchmark::kNanosecond); \
+  void BENCHMARK_csa_with_arith_autovec_##ty##_(benchmark::State &state) {     \
+    benchmark_csa_autovec<ty>(state, run_csa_with_arith_autovec,               \
+                              run_csa_with_arith_novec, Threshold);            \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_csa_with_arith_autovec_##ty##_)->Unit(                   \
+                                                      benchmark::kNanosecond); \
+                                                                               \
+  void BENCHMARK_csa_with_arith_novec_##ty##_(benchmark::State &state) {       \
+    benchmark_csa_novec<ty>(state, run_csa_with_arith_novec, Threshold);       \
+  }                                                                            \
+  BENCHMARK(BENCHMARK_csa_with_arith_novec_##ty##_)->Unit(                     \
+                                                        benchmark::kNanosecond);
+
+ADD_BENCHMARK(int32_t, 75)
+ADD_BENCHMARK(uint8_t, 90)
+ADD_BENCHMARK(int64_t, 60)