Add transpose test.

test/test_linalg.py

@@ -150,6 +150,54 @@ def test_axpy(ctx_factory):
 
 
 
+def test_transpose(ctx_factory):
+    dtype = np.float32
+    ctx = ctx_factory()
+    order = "C"
+    queue = cl.CommandQueue(ctx,
+            properties=cl.command_queue_properties.PROFILING_ENABLE)
+
+    n = get_suitable_size(ctx)
+
+    knl = lp.make_kernel(ctx.devices[0],
+            "{[i,j]: 0<=i,j<%d}" % n,
+            [
+                "b[i, j] = a[j, i]"
+                ],
+            [
+                lp.ArrayArg("a", dtype, shape=(n, n), order=order),
+                lp.ArrayArg("b", dtype, shape=(n, n), order=order),
+                ],
+            name="transpose")
+
+    knl = lp.split_dimension(knl, "i", 16,
+            outer_tag="g.0", inner_tag="l.1")
+    knl = lp.split_dimension(knl, "j", 16,
+            outer_tag="g.1", inner_tag="l.0")
+    knl = lp.add_prefetch(knl, 'a', ["i_inner", "j_inner"])
+    knl = lp.add_prefetch(knl, 'b', ["j_inner", "k_inner", ])
+
+    kernel_gen = lp.generate_loop_schedules(knl)
+    kernel_gen = lp.check_kernels(kernel_gen, {}, kill_level_min=5)
+
+    a = make_well_conditioned_dev_matrix(queue, n, dtype=dtype, order=order)
+    b = cl_array.empty_like(a)
+    refsol = a.get().T.copy()
+
+    def launcher(kernel, gsize, lsize, check):
+        evt = kernel(queue, gsize(), lsize(), a.data, b.data,
+                g_times_l=True)
+
+        if check:
+            check_error(refsol, b.get())
+
+        return evt
+
+    lp.drive_timing_run(kernel_gen, queue, launcher, 0)
+
+
+
+
 def test_plain_matrix_mul(ctx_factory):
     dtype = np.float32
     ctx = ctx_factory()
@@ -838,47 +886,7 @@ def main_elwise_scaled_matrix_mul():
 
 
 
-def main_transpose():
-    n = 16*48
-    from pymbolic import var
-    a, b, i, j = [var(s) for s in "abij"]
-
-    k = make_loop_kernel([
-        LoopDimension("i", n),
-        LoopDimension("j", n),
-        ], [
-        (b[i+n*j], a[j+n*i])
-        ])
-
-    gen_kwargs = {
-            "min_threads": 128,
-            "min_blocks": 32,
-            }
-
-    if True and HAVE_CUDA:
-        if HAVE_CUDA:
-            a = curandom.rand((n, n))
-            b = gpuarray.empty_like(a)
-
-        def launcher(grid, kernel, texref_lookup):
-            a.bind_to_texref_ext(texref_lookup["a"])
-            kernel.prepared_call(grid, b.gpudata)
-
-        drive_timing_run(
-                generate_all_kernels(k, **gen_kwargs),
-                launcher, 0)
-    else:
-        show_kernel_codes(generate_all_kernels(k, **gen_kwargs))
-
-
-
-
-
 if __name__ == "__main__":
-    # make sure that import failures get reported, instead of skipping the
-    # tests.
-    import pyopencl as cl
-
     import sys
     if len(sys.argv) > 1:
         exec(sys.argv[1])