From 51bb43c6fc3fd3175dd2fe37b0b202c05e5c944e Mon Sep 17 00:00:00 2001
From: Kaushik Kulkarni <kaushikcfd@gmail.com>
Date: Thu, 3 Mar 2022 14:37:16 -0600
Subject: [PATCH] test c vector extensions

---
 test/test_target.py | 89 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 89 insertions(+)

diff --git a/test/test_target.py b/test/test_target.py
index a7e838785..51c2cb16a 100644
--- a/test/test_target.py
+++ b/test/test_target.py
@@ -737,6 +737,95 @@ def test_non_executable_targets_respect_args():
         assert code_str.find(f"double const *__restrict__ {var}") != -1
 
 
+def test_c_vector_extensions():
+    knl = lp.make_kernel(
+        "{[i, j1, j2, j3]: 0<=i<10 and 0<=j1,j2,j3<4}",
+        """
+        <> temp1[j1] = x[i, j1]
+        <> temp2[j2] = 2*temp1[j2] + 1 {inames=i:j2}
+        y[i, j3] = temp2[j3]
+        """,
+        [lp.GlobalArg("x, y", shape=lp.auto, dtype=float)],
+        seq_dependencies=True,
+        target=lp.CVectorExtensionsTarget())
+
+    knl = lp.tag_inames(knl, "j2:vec, j1:ilp, j3:ilp")
+    knl = lp.tag_array_axes(knl, "temp1,temp2", "vec")
+
+    print(lp.generate_code_v2(knl).device_code())
+
+
+def test_omp_simd_tag():
+    knl = lp.make_kernel(
+        "{[i]: 0<=i<16}",
+        """
+        y[i] = 2 * x[i]
+        """)
+
+    knl = lp.add_dtypes(knl, {"x": "float64"})
+    knl = lp.split_iname(knl, "i", 4)
+    knl = lp.tag_inames(knl, {"i_inner": lp.OpenMPSIMDTag()})
+
+    code_str = lp.generate_code_v2(knl).device_code()
+
+    assert any(line.strip() == "#pragma omp simd"
+               for line in code_str.split("\n"))
+
+
+def test_vec_tag_with_omp_simd_fallback():
+    knl = lp.make_kernel(
+        "{[i, j1, j2, j3]: 0<=i<10 and 0<=j1,j2,j3<4}",
+        """
+        <> temp1[j1] = x[i, j1]
+        <> temp2[j2] = 2*temp1[j2] + 1 {inames=i:j2}
+        y[i, j3] = temp2[j3]
+        """,
+        [lp.GlobalArg("x, y", shape=lp.auto, dtype=float)],
+        seq_dependencies=True,
+        target=lp.ExecutableCVectorExtensionsTarget())
+
+    knl = lp.tag_inames(knl, {"j1": lp.VectorizeTag(lp.OpenMPSIMDTag()),
+                              "j2": lp.VectorizeTag(lp.OpenMPSIMDTag()),
+                              "j3": lp.VectorizeTag(lp.OpenMPSIMDTag())})
+    knl = lp.tag_array_axes(knl, "temp1,temp2", "vec")
+
+    code_str = lp.generate_code_v2(knl).device_code()
+
+    assert len([line
+                for line in code_str.split("\n")
+                if line.strip() == "#pragma omp simd"]) == 2
+
+    x = np.random.rand(10, 4)
+    _, (out,) = knl(x=x)
+    np.testing.assert_allclose(out, 2*x+1)
+
+
+def test_vec_extensions_with_multiple_loopy_body_insns():
+    knl = lp.make_kernel(
+        "{[n]: 0<=n<N}",
+        """
+        for n
+            ... nop          {id=expr_start}
+            <> tmp = 2.0
+            dat0[n, 0] = tmp {id=expr_insn}
+            ... nop          {id=statement0}
+        end
+        """,
+        seq_dependencies=True,
+        target=lp.ExecutableCVectorExtensionsTarget())
+
+    knl = lp.add_dtypes(knl, {"dat0": "float64"})
+    knl = lp.split_iname(knl, "n", 4, slabs=(1, 1),
+                         inner_iname="n_batch")
+    knl = lp.privatize_temporaries_with_inames(knl, "n_batch")
+    knl = lp.tag_array_axes(knl, "tmp", "vec")
+    knl = lp.tag_inames(knl, {
+        "n_batch": lp.VectorizeTag(lp.OpenMPSIMDTag())})
+
+    _, (out,) = knl(N=100)
+    np.testing.assert_allclose(out, 2*np.ones((100, 1)))
+
+
 if __name__ == "__main__":
     if len(sys.argv) > 1:
         exec(sys.argv[1])