Merge pull request #69 from r-devulap/fix-warnings

Fix compiler warnings in src and tests
intel · Sep 6, 2023 · ed6c409 · ed6c409
2 parents 94280b1 + 9cecdcb
commit ed6c409
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Showing 7 changed files with 45 additions and 42 deletions.
diff --git a/Makefile b/Makefile
@@ -46,7 +46,7 @@ BENCHOBJS := $(patsubst %.cpp, %.o, $(filter-out $(addprefix $(BENCHDIR)/, $(BEN
 TESTOBJS := $(patsubst %.cpp, %.o, $(filter-out $(addprefix $(TESTDIR)/, $(TESTS_SKIP)), $(TESTS)))
 UTILOBJS := $(UTILS:.cpp=.o)
 
-# Stops make from wondering if it needs to generate the .hpp files (.cpp and .h have equivalent rules by default) 
+# Stops make from wondering if it needs to generate the .hpp files (.cpp and .h have equivalent rules by default)
 %.hpp:
 
 .PHONY: all
@@ -75,7 +75,7 @@ benchexe: $(BENCHOBJS) $(UTILOBJS)
 
 .PHONY: meson
 meson:
- meson setup --warnlevel 0 --buildtype plain builddir
+ meson setup --warnlevel 2 --buildtype plain builddir
  cd builddir && ninja
 
 .PHONY: clean

diff --git a/src/avx512-64bit-argsort.hpp b/src/avx512-64bit-argsort.hpp
@@ -108,7 +108,7 @@ X86_SIMD_SORT_INLINE void argsort_32_64bit(type_t *arr, int64_t *arg, int32_t N)
  zmm_t arrzmm[4];
  argzmm_t argzmm[4];
 
-#pragma X86_SIMD_SORT_UNROLL_LOOP(2)
+X86_SIMD_SORT_UNROLL_LOOP(2)
  for (int ii = 0; ii < 2; ++ii) {
  argzmm[ii] = argtype::loadu(arg + 8 * ii);
  arrzmm[ii] = vtype::template i64gather<sizeof(type_t)>(argzmm[ii], arr);
@@ -117,7 +117,7 @@ X86_SIMD_SORT_INLINE void argsort_32_64bit(type_t *arr, int64_t *arg, int32_t N)
 
  uint64_t combined_mask = (0x1ull << (N - 16)) - 0x1ull;
  opmask_t load_mask[2] = {0xFF, 0xFF};
-#pragma X86_SIMD_SORT_UNROLL_LOOP(2)
+X86_SIMD_SORT_UNROLL_LOOP(2)
  for (int ii = 0; ii < 2; ++ii) {
  load_mask[ii] = (combined_mask >> (ii * 8)) & 0xFF;
  argzmm[ii + 2] = argtype::maskz_loadu(load_mask[ii], arg + 16 + 8 * ii);
@@ -151,7 +151,7 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
  zmm_t arrzmm[8];
  argzmm_t argzmm[8];
 
-#pragma X86_SIMD_SORT_UNROLL_LOOP(4)
+X86_SIMD_SORT_UNROLL_LOOP(4)
  for (int ii = 0; ii < 4; ++ii) {
  argzmm[ii] = argtype::loadu(arg + 8 * ii);
  arrzmm[ii] = vtype::template i64gather<sizeof(type_t)>(argzmm[ii], arr);
@@ -160,7 +160,7 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
 
  opmask_t load_mask[4] = {0xFF, 0xFF, 0xFF, 0xFF};
  uint64_t combined_mask = (0x1ull << (N - 32)) - 0x1ull;
-#pragma X86_SIMD_SORT_UNROLL_LOOP(4)
+X86_SIMD_SORT_UNROLL_LOOP(4)
  for (int ii = 0; ii < 4; ++ii) {
  load_mask[ii] = (combined_mask >> (ii * 8)) & 0xFF;
  argzmm[ii + 4] = argtype::maskz_loadu(load_mask[ii], arg + 32 + 8 * ii);
@@ -170,7 +170,7 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
  argzmm[ii + 4]);
  }
 
-#pragma X86_SIMD_SORT_UNROLL_LOOP(4)
+X86_SIMD_SORT_UNROLL_LOOP(4)
  for (int ii = 0; ii < 8; ii = ii + 2) {
  bitonic_merge_two_zmm_64bit<vtype, argtype>(
  arrzmm[ii], arrzmm[ii + 1], argzmm[ii], argzmm[ii + 1]);
@@ -179,11 +179,11 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
  bitonic_merge_four_zmm_64bit<vtype, argtype>(arrzmm + 4, argzmm + 4);
  bitonic_merge_eight_zmm_64bit<vtype, argtype>(arrzmm, argzmm);
 
-#pragma X86_SIMD_SORT_UNROLL_LOOP(4)
+X86_SIMD_SORT_UNROLL_LOOP(4)
  for (int ii = 0; ii < 4; ++ii) {
  argtype::storeu(arg + 8 * ii, argzmm[ii]);
  }
-#pragma X86_SIMD_SORT_UNROLL_LOOP(4)
+X86_SIMD_SORT_UNROLL_LOOP(4)
  for (int ii = 0; ii < 4; ++ii) {
  argtype::mask_storeu(arg + 32 + 8 * ii, load_mask[ii], argzmm[ii + 4]);
  }
@@ -203,7 +203,7 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
 // zmm_t arrzmm[16];
 // argzmm_t argzmm[16];
 //
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 8; ++ii) {
 // argzmm[ii] = argtype::loadu(arg + 8*ii);
 // arrzmm[ii] = vtype::template i64gather<sizeof(type_t)>(argzmm[ii], arr);
@@ -213,19 +213,19 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
 // opmask_t load_mask[8] = {0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF};
 // if (N != 128) {
 // uint64_t combined_mask = (0x1ull << (N - 64)) - 0x1ull;
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 8; ++ii) {
 // load_mask[ii] = (combined_mask >> (ii*8)) & 0xFF;
 // }
 // }
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 8; ++ii) {
 // argzmm[ii+8] = argtype::maskz_loadu(load_mask[ii], arg + 64 + 8*ii);
 // arrzmm[ii+8] = vtype::template mask_i64gather<sizeof(type_t)>(vtype::zmm_max(), load_mask[ii], argzmm[ii+8], arr);
 // arrzmm[ii+8] = sort_zmm_64bit<vtype, argtype>(arrzmm[ii+8], argzmm[ii+8]);
 // }
 //
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 16; ii = ii + 2) {
 // bitonic_merge_two_zmm_64bit<vtype, argtype>(arrzmm[ii], arrzmm[ii + 1], argzmm[ii], argzmm[ii + 1]);
 // }
@@ -237,11 +237,11 @@ X86_SIMD_SORT_INLINE void argsort_64_64bit(type_t *arr, int64_t *arg, int32_t N)
 // bitonic_merge_eight_zmm_64bit<vtype, argtype>(arrzmm+8, argzmm+8);
 // bitonic_merge_sixteen_zmm_64bit<vtype, argtype>(arrzmm, argzmm);
 //
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 8; ++ii) {
 // argtype::storeu(arg + 8*ii, argzmm[ii]);
 // }
-//#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+//X86_SIMD_SORT_UNROLL_LOOP(8)
 // for (int ii = 0; ii < 8; ++ii) {
 // argtype::mask_storeu(arg + 64 + 8*ii, load_mask[ii], argzmm[ii + 8]);
 // }

diff --git a/src/avx512-common-argsort.h b/src/avx512-common-argsort.h
@@ -198,7 +198,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  // first and last vtype::numlanes values are partitioned at the end
  zmm_t vec_left[num_unroll], vec_right[num_unroll];
  argzmm_t argvec_left[num_unroll], argvec_right[num_unroll];
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  argvec_left[ii] = argtype::loadu(arg + left + vtype::numlanes * ii);
  vec_left[ii] = vtype::template i64gather<sizeof(type_t)>(
@@ -224,7 +224,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  */
  if ((r_store + vtype::numlanes) - right < left - l_store) {
  right -= num_unroll * vtype::numlanes;
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  arg_vec[ii]
  = argtype::loadu(arg + right + ii * vtype::numlanes);
@@ -233,7 +233,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  }
  }
  else {
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  arg_vec[ii] = argtype::loadu(arg + left + ii * vtype::numlanes);
  curr_vec[ii] = vtype::template i64gather<sizeof(type_t)>(
@@ -242,7 +242,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  left += num_unroll * vtype::numlanes;
  }
  // partition the current vector and save it on both sides of the array
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_gt_pivot
  = partition_vec<vtype>(arg,
@@ -259,7 +259,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  }
 
  /* partition and save vec_left and vec_right */
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_gt_pivot
  = partition_vec<vtype>(arg,
@@ -273,7 +273,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  l_store += (vtype::numlanes - amount_gt_pivot);
  r_store -= amount_gt_pivot;
  }
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_gt_pivot
  = partition_vec<vtype>(arg,

diff --git a/src/avx512-common-qsort.h b/src/avx512-common-qsort.h
@@ -67,6 +67,8 @@
 #define ZMM_MAX_INT16 _mm512_set1_epi16(X86_SIMD_SORT_MAX_INT16)
 #define SHUFFLE_MASK(a, b, c, d) (a << 6) | (b << 4) | (c << 2) | d
 
+#define PRAGMA(x) _Pragma (#x)
+
 /* Compiler specific macros specific */
 #ifdef _MSC_VER
 #define X86_SIMD_SORT_INLINE static inline
@@ -93,8 +95,7 @@
 #endif
 
 #if __GNUC__ >= 8
-#define X86_SIMD_SORT_UNROLL_LOOP(num)\
-GCC unroll num
+#define X86_SIMD_SORT_UNROLL_LOOP(num) PRAGMA(GCC unroll num)
 #else
 #define X86_SIMD_SORT_UNROLL_LOOP(num)
 #endif
@@ -393,7 +394,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  // We will now have atleast 16 registers worth of data to process:
  // left and right vtype::numlanes values are partitioned at the end
  zmm_t vec_left[num_unroll], vec_right[num_unroll];
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  vec_left[ii] = vtype::loadu(arr + left + vtype::numlanes * ii);
  vec_right[ii] = vtype::loadu(
@@ -414,20 +415,20 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  */
  if ((r_store + vtype::numlanes) - right < left - l_store) {
  right -= num_unroll * vtype::numlanes;
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  curr_vec[ii] = vtype::loadu(arr + right + ii * vtype::numlanes);
  }
  }
  else {
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  curr_vec[ii] = vtype::loadu(arr + left + ii * vtype::numlanes);
  }
  left += num_unroll * vtype::numlanes;
  }
 // partition the current vector and save it on both sides of the array
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_ge_pivot
  = partition_vec<vtype>(arr,
@@ -443,7 +444,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  }
 
 /* partition and save vec_left[8] and vec_right[8] */
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_ge_pivot
  = partition_vec<vtype>(arr,
@@ -456,7 +457,7 @@ static inline int64_t partition_avx512_unrolled(type_t *arr,
  l_store += (vtype::numlanes - amount_ge_pivot);
  r_store -= amount_ge_pivot;
  }
-#pragma X86_SIMD_SORT_UNROLL_LOOP(8)
+X86_SIMD_SORT_UNROLL_LOOP(8)
  for (int ii = 0; ii < num_unroll; ++ii) {
  int32_t amount_ge_pivot
  = partition_vec<vtype>(arr,

diff --git a/tests/test-argselect.hpp b/tests/test-argselect.hpp
@@ -29,13 +29,15 @@ TYPED_TEST_P(avx512argselect, test_random)
  = avx512_argselect<TypeParam>(arr.data(), k, arr.size());
  auto true_kth = arr[sorted_inx[k]];
  EXPECT_EQ(true_kth, arr[inx[k]]) << "Failed at index k = " << k;
- if (k >= 1)
+ if (k >= 1) {
  EXPECT_GE(true_kth, std_max_element(arr, inx, 0, k - 1))
  << "failed at k = " << k;
- if (k != arrsize - 1)
+ }
+ if (k != arrsize - 1) {
  EXPECT_LE(true_kth,
  std_min_element(arr, inx, k + 1, arrsize - 1))
  << "failed at k = " << k;
+ }
  EXPECT_UNIQUE(inx)
  }
  }

diff --git a/tests/test-argsort.hpp b/tests/test-argsort.hpp
@@ -23,7 +23,7 @@ TYPED_TEST_P(avx512argsort, test_random)
  std::vector<int64_t> inx2
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1, sort2;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx1[jj]]);
  sort2.push_back(arr[inx2[jj]]);
  }
@@ -48,14 +48,14 @@ TYPED_TEST_P(avx512argsort, test_constant)
  for (auto &size : arrsizes) {
  /* constant array */
  auto elem = get_uniform_rand_array<TypeParam>(1)[0];
- for (int64_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  arr.push_back(elem);
  }
  std::vector<int64_t> inx1 = std_argsort(arr);
  std::vector<int64_t> inx2
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1, sort2;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx1[jj]]);
  sort2.push_back(arr[inx2[jj]]);
  }
@@ -84,7 +84,7 @@ TYPED_TEST_P(avx512argsort, test_small_range)
  std::vector<int64_t> inx2
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1, sort2;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx1[jj]]);
  sort2.push_back(arr[inx2[jj]]);
  }
@@ -113,7 +113,7 @@ TYPED_TEST_P(avx512argsort, test_sorted)
  std::vector<int64_t> inx2
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1, sort2;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx1[jj]]);
  sort2.push_back(arr[inx2[jj]]);
  }
@@ -143,7 +143,7 @@ TYPED_TEST_P(avx512argsort, test_reverse)
  std::vector<int64_t> inx2
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1, sort2;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx1[jj]]);
  sort2.push_back(arr[inx2[jj]]);
  }
@@ -177,7 +177,7 @@ TYPED_TEST_P(avx512argsort, test_array_with_nan)
  std::vector<int64_t> inx
  = avx512_argsort<TypeParam>(arr.data(), arr.size());
  std::vector<TypeParam> sort1;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sort1.push_back(arr[inx[jj]]);
  }
  if ((!std::isnan(sort1[size - 1])) || (!std::isnan(sort1[size - 2]))) {
@@ -211,7 +211,7 @@ TYPED_TEST_P(avx512argsort, test_max_value_at_end_of_array)
  }
  std::vector<int64_t> inx = avx512_argsort(arr.data(), arr.size());
  std::vector<TypeParam> sorted;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sorted.push_back(arr[inx[jj]]);
  }
  if (!std::is_sorted(sorted.begin(), sorted.end())) {
@@ -250,7 +250,7 @@ TYPED_TEST_P(avx512argsort, test_all_inf_array)
  }
  std::vector<int64_t> inx = avx512_argsort(arr.data(), arr.size());
  std::vector<TypeParam> sorted;
- for (size_t jj = 0; jj < size; ++jj) {
+ for (auto jj = 0; jj < size; ++jj) {
  sorted.push_back(arr[inx[jj]]);
  }
  if (!std::is_sorted(sorted.begin(), sorted.end())) {

diff --git a/tests/test-partial-qsort.hpp b/tests/test-partial-qsort.hpp
@@ -24,7 +24,7 @@ TYPED_TEST_P(avx512_partial_sort, test_ranges)
  /* Sort with std::sort for comparison */
  std::sort(sortedarr.begin(), sortedarr.end());
 
- for (size_t ii = 0; ii < nranges; ++ii) {
+ for (auto ii = 0; ii < nranges; ++ii) {
  psortedarr = arr;
 
  /* Pick a random number of elements to sort at the beginning of the array */
@@ -33,7 +33,7 @@ TYPED_TEST_P(avx512_partial_sort, test_ranges)
  /* Sort the range and verify all the required elements match the presorted set */
  avx512_partial_qsort<TypeParam>(
  psortedarr.data(), k, psortedarr.size());
- for (size_t jj = 0; jj < k; jj++) {
+ for (auto jj = 0; jj < k; jj++) {
  ASSERT_EQ(sortedarr[jj], psortedarr[jj]);
  }