Optimize the performance of multiply

1 files changed, 91 insertions, 102 deletions

diff --git a/numpy/core/src/multiarray/einsum_sumprod.c.src b/numpy/core/src/multiarray/einsum_sumprod.c.src
index c58e74287..f5478bf8f 100644
--- a/numpy/core/src/multiarray/einsum_sumprod.c.src
+++ b/numpy/core/src/multiarray/einsum_sumprod.c.src
@@ -17,7 +17,8 @@
 
 #include "einsum_sumprod.h"
 #include "einsum_debug.h"
-
+#include "simd/simd.h"
+#include "common.h"
 
 #ifdef NPY_HAVE_SSE_INTRINSICS
 #define EINSUM_USE_SSE1 1
@@ -41,6 +42,28 @@
 
 #define EINSUM_IS_SSE_ALIGNED(x) ((((npy_intp)x)&0xf) == 0)
 
+// ARM/Neon don't have instructions for aligned memory access
+#ifdef NPY_HAVE_NEON
+    #define EINSUM_IS_ALIGNED(x) 0
+#else
+    #define EINSUM_IS_ALIGNED(x) npy_is_aligned(x, NPY_SIMD_WIDTH)
+#endif
+
+/**
+ * This macro is used to enable a scalar loop which advances 4 elements at a
+ * time, which appears after a main SIMD loop gated by `CHK` that unrolls by
+ * `NPY_SIMD_WIDTH * unroll_by` elements, and before a non-unrolled scalar loop
+ * that finishes up all the remaining scalars. The purpose of the unrolled loop
+ * is to enable auto-vectorization in cases when all of the following are true:
+ *
+ *  - optimization is allowed
+ *  - either:
+ *    - we did not run the SIMD loop at all, due to NPV being disabled.
+ *    - the SIMD loop was larger than 128bit, so there are likely to be many
+ *      elements left to process.
+ */
+#define EINSUM_UNROLL_4_SCALARS(CHK) (!defined(NPY_DISABLE_OPTIMIZATION) && (!(CHK) || NPY_SIMD > 128))
+
 /**********************************************/
 
 /**begin repeat
@@ -56,6 +79,10 @@
  *             npy_ubyte, npy_ushort, npy_uint, npy_ulong, npy_ulonglong,
  *             npy_float, npy_float, npy_double, npy_longdouble,
  *             npy_float, npy_double, npy_longdouble#
+ * #sfx  = s8, s16, s32, long, s64,
+ *        u8, u16, u32, ulong, u64,
+ *        half, f32, f64, longdouble,
+ *        f32, f64, clongdouble#
  * #to = ,,,,,
  *       ,,,,,
  *       npy_float_to_half,,,,
@@ -76,6 +103,10 @@
  *            0*5,
  *            0,0,1,0,
  *            0*3#
+ * #NPYV_CHK = 0*5,
+ *             0*5,
+ *             0, NPY_SIMD, NPY_SIMD_F64, 0,
+ *             0*3#
  */
 
 /**begin repeat1
@@ -250,115 +281,73 @@ static void
     @type@ *data0 = (@type@ *)dataptr[0];
     @type@ *data1 = (@type@ *)dataptr[1];
     @type@ *data_out = (@type@ *)dataptr[2];
-
-#if EINSUM_USE_SSE1 && @float32@
-    __m128 a, b;
-#elif EINSUM_USE_SSE2 && @float64@
-    __m128d a, b;
-#endif
-
     NPY_EINSUM_DBG_PRINT1("@name@_sum_of_products_contig_two (%d)\n",
                                                             (int)count);
-
-/* This is placed before the main loop to make small counts faster */
-finish_after_unrolled_loop:
-    switch (count) {
-/**begin repeat2
- * #i = 6, 5, 4, 3, 2, 1, 0#
- */
-        case @i@+1:
-            data_out[@i@] = @to@(@from@(data0[@i@]) *
-                                 @from@(data1[@i@]) +
-                                 @from@(data_out[@i@]));
-/**end repeat2**/
-        case 0:
-            return;
-    }
-
-#if EINSUM_USE_SSE1 && @float32@
+    // NPYV check for @type@, in X86, 128bits intrinsincs have a side effect in optimization
+#if @NPYV_CHK@
     /* Use aligned instructions if possible */
-    if (EINSUM_IS_SSE_ALIGNED(data0) && EINSUM_IS_SSE_ALIGNED(data1) &&
-        EINSUM_IS_SSE_ALIGNED(data_out)) {
-        /* Unroll the loop by 8 */
-        while (count >= 8) {
-            count -= 8;
-
-/**begin repeat2
- * #i = 0, 4#
- */
-            a = _mm_mul_ps(_mm_load_ps(data0+@i@), _mm_load_ps(data1+@i@));
-            b = _mm_add_ps(a, _mm_load_ps(data_out+@i@));
-            _mm_store_ps(data_out+@i@, b);
-/**end repeat2**/
-            data0 += 8;
-            data1 += 8;
-            data_out += 8;
+    const int is_aligned = EINSUM_IS_ALIGNED(data0) && EINSUM_IS_ALIGNED(data1) &&
+                        EINSUM_IS_ALIGNED(data_out);
+    const int vstep = npyv_nlanes_@sfx@;
+
+    /**begin repeat2
+     * #cond = if(is_aligned), else#
+     * #ld = loada, load#
+     * #st = storea, store#
+     */
+    @cond@ {
+        const npy_intp vstepx4 = vstep * 4;
+        for (; count >= vstepx4; count -= vstepx4, data0 += vstepx4, data1 += vstepx4, data_out += vstepx4) {
+            /**begin repeat3
+             * #i = 0, 1, 2, 3#
+             */
+            npyv_@sfx@ a@i@ = npyv_@ld@_@sfx@(data0 + vstep * @i@);
+            npyv_@sfx@ b@i@ = npyv_@ld@_@sfx@(data1 + vstep * @i@);
+            npyv_@sfx@ c@i@ = npyv_@ld@_@sfx@(data_out + vstep * @i@);
+            /**end repeat3**/
+            /**begin repeat3
+             * #i = 0, 1, 2, 3#
+             */
+            npyv_@sfx@ abc@i@ = npyv_muladd_@sfx@(a@i@, b@i@, c@i@);
+            /**end repeat3**/
+            /**begin repeat3
+             * #i = 0, 1, 2, 3#
+             */
+            npyv_@st@_@sfx@(data_out + vstep * @i@, abc@i@);
+            /**end repeat3**/
         }
-
-        /* Finish off the loop */
-        goto finish_after_unrolled_loop;
     }
-#elif EINSUM_USE_SSE2 && @float64@
-    /* Use aligned instructions if possible */
-    if (EINSUM_IS_SSE_ALIGNED(data0) && EINSUM_IS_SSE_ALIGNED(data1) &&
-        EINSUM_IS_SSE_ALIGNED(data_out)) {
-        /* Unroll the loop by 8 */
-        while (count >= 8) {
-            count -= 8;
-
-/**begin repeat2
- * #i = 0, 2, 4, 6#
- */
-            a = _mm_mul_pd(_mm_load_pd(data0+@i@), _mm_load_pd(data1+@i@));
-            b = _mm_add_pd(a, _mm_load_pd(data_out+@i@));
-            _mm_store_pd(data_out+@i@, b);
-/**end repeat2**/
-            data0 += 8;
-            data1 += 8;
-            data_out += 8;
-        }
-
-        /* Finish off the loop */
-        goto finish_after_unrolled_loop;
+    /**end repeat2**/
+    npyv_cleanup();
+#endif // NPYV check for @type@
+
+#if EINSUM_UNROLL_4_SCALARS(@NPYV_CHK@)
+    for (; count >= 4; count -= 4, data0 += 4, data1 += 4, data_out += 4) {
+        /**begin repeat2
+         * #i = 0, 1, 2, 3#
+         */
+        const @type@ a@i@ = @from@(data0[@i@]);
+        const @type@ b@i@ = @from@(data1[@i@]);
+        const @type@ c@i@ = @from@(data_out[@i@]);
+        /**end repeat2**/
+        /**begin repeat2
+         * #i = 0, 1, 2, 3#
+         */
+        const @type@ abc@i@ = a@i@ * b@i@ + c@i@;
+        /**end repeat2**/
+        /**begin repeat2
+         * #i = 0, 1, 2, 3#
+         */
+        data_out[@i@] = @to@(abc@i@);
+        /**end repeat2**/
     }
 #endif
-
-    /* Unroll the loop by 8 */
-    while (count >= 8) {
-        count -= 8;
-
-#if EINSUM_USE_SSE1 && @float32@
-/**begin repeat2
- * #i = 0, 4#
- */
-        a = _mm_mul_ps(_mm_loadu_ps(data0+@i@), _mm_loadu_ps(data1+@i@));
-        b = _mm_add_ps(a, _mm_loadu_ps(data_out+@i@));
-        _mm_storeu_ps(data_out+@i@, b);
-/**end repeat2**/
-#elif EINSUM_USE_SSE2 && @float64@
-/**begin repeat2
- * #i = 0, 2, 4, 6#
- */
-        a = _mm_mul_pd(_mm_loadu_pd(data0+@i@), _mm_loadu_pd(data1+@i@));
-        b = _mm_add_pd(a, _mm_loadu_pd(data_out+@i@));
-        _mm_storeu_pd(data_out+@i@, b);
-/**end repeat2**/
-#else
-/**begin repeat2
- * #i = 0, 1, 2, 3, 4, 5, 6, 7#
- */
-        data_out[@i@] = @to@(@from@(data0[@i@]) *
-                             @from@(data1[@i@]) +
-                             @from@(data_out[@i@]));
-/**end repeat2**/
-#endif
-        data0 += 8;
-        data1 += 8;
-        data_out += 8;
+    for (; count > 0; --count, ++data0, ++data1, ++data_out) {
+        const @type@ a = @from@(*data0);
+        const @type@ b = @from@(*data1);
+        const @type@ c = @from@(*data_out);
+        *data_out = @to@(a * b + c);
     }
-
-    /* Finish off the loop */
-    goto finish_after_unrolled_loop;
 }
 
 /* Some extra specializations for the two operand case */