From d68e69a863923d46219d957d726b51b34f0884a3 Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Fri, 2 Mar 2012 13:24:32 -0600
Subject: [PATCH] Add SEM test case from Reagan airport with Tim.
---
test/test_sem_reagan.py | 117 ++++++++++++++++++++++++++++++++++++++++
1 file changed, 117 insertions(+)
create mode 100644 test/test_sem_reagan.py
diff --git a/test/test_sem_reagan.py b/test/test_sem_reagan.py
new file mode 100644
index 000000000..8d31024bb
--- /dev/null
+++ b/test/test_sem_reagan.py
@@ -0,0 +1,117 @@
+from __future__ import division
+
+import numpy as np
+import pyopencl as cl
+import loopy as lp
+
+from pyopencl.tools import pytest_generate_tests_for_pyopencl \
+ as pytest_generate_tests
+
+
+
+
+def test_tim2d(ctx_factory):
+ dtype = np.float32
+ ctx = ctx_factory()
+ order = "C"
+
+ n = 8
+
+ from pymbolic import var
+ K_sym = var("K")
+
+ field_shape = (K_sym, n, n)
+
+ # K - run-time symbolic
+ knl = lp.make_kernel(ctx.devices[0],
+ "[K] -> {[i,j,e,m,o,gi]: 0<=i,j,m,o<%d and 0<=e<K and 0<=gi<3}" % n,
+ [
+ "ur(a,b) := sum_float32(@o, D[a,o]*u[e,o,b])",
+ "us(a,b) := sum_float32(@o, D[b,o]*u[e,a,o])",
+
+ #"Gu(mat_entry,a,b) := G[mat_entry,e,m,j]*ur(m,j)",
+
+ "Gux(a,b) := G[0,e,a,b]*ur(a,b)+G[1,e,a,b]*us(a,b)",
+ "Guy(a,b) := G[1,e,a,b]*ur(a,b)+G[2,e,a,b]*us(a,b)",
+ "lap[e,i,j] = "
+ " sum_float32(m, D[m,i]*Gux(m,j))"
+ "+ sum_float32(m, D[m,j]*Guy(i,m))"
+
+ ],
+ [
+ lp.ArrayArg("u", dtype, shape=field_shape, order=order),
+ lp.ArrayArg("lap", dtype, shape=field_shape, order=order),
+ lp.ArrayArg("G", dtype, shape=(3,)+field_shape, order=order),
+ # lp.ConstantArrayArg("D", dtype, shape=(n, n), order=order),
+ lp.ArrayArg("D", dtype, shape=(n, n), order=order),
+ # lp.ImageArg("D", dtype, shape=(n, n)),
+ lp.ScalarArg("K", np.int32, approximately=1000),
+ ],
+ name="semlap2D", assumptions="K>=1")
+
+ seq_knl = knl
+
+ def variant_orig(knl):
+ knl = lp.add_prefetch(knl, "D", ["m", "j", "i","o"])
+ knl = lp.add_prefetch(knl, "u", ["i", "j", "o"])
+ knl = lp.precompute(knl, "ur", np.float32, ["a", "b"])
+ knl = lp.precompute(knl, "us", np.float32, ["a", "b"])
+ knl = lp.split_dimension(knl, "e", 1, outer_tag="g.0")#, slabs=(0, 1))
+
+ knl = lp.tag_dimensions(knl, dict(i="l.0", j="l.1"))
+ knl = lp.tag_dimensions(knl, dict(o="unr"))
+ knl = lp.tag_dimensions(knl, dict(m="unr"))
+
+
+ # knl = lp.add_prefetch(knl, "G", [2,3], default_tag=None) # axis/argument indices on G
+ knl = lp.add_prefetch(knl, "G", [2,3]) # axis/argument indices on G
+
+ def variant_prefetch(knl):
+ knl = lp.precompute(knl, "ur", np.float32, ["a", "b"])
+ knl = lp.precompute(knl, "us", np.float32, ["a", "b"])
+ return knl
+
+ def variant_1(knl):
+ # BUG? why can't the prefetch be in the j loop??!
+ print knl
+ from pudb import set_trace; set_trace()
+ knl = lp.precompute(knl, "ur", np.float32, ["a"])
+ print knl
+ 1/0
+ #knl = lp.precompute(knl, "us", np.float32, ["a"])
+ return knl
+
+ def variant_g_prefetch(knl):
+ knl = lp.precompute(knl, "ur", np.float32, ["a"])
+ knl = lp.precompute(knl, "us", np.float32, ["a"])
+ knl = lp.add_prefetch(knl, "G", per_access=True) # IMPLEMENT!
+ return knl
+
+ def variant_gu_precomp(knl):
+ knl = lp.precompute(knl, "ur", np.float32, ["a"])
+ knl = lp.precompute(knl, "us", np.float32, ["a"])
+ knl = lp.precompute(knl, "Gux", np.float32, ["a", "b"])
+ knl = lp.precompute(knl, "Guy", np.float32, ["a", "b"])
+ return knl
+
+ #for variant in [variant_orig]:
+ for variant in [variant_1]:
+ kernel_gen = lp.generate_loop_schedules(variant(knl))
+ kernel_gen = lp.check_kernels(kernel_gen, dict(K=1000))
+
+ K = 1000
+ lp.auto_test_vs_ref(seq_knl, ctx, kernel_gen,
+ op_count=K*(n*n*n*2*2 + n*n*2*3 + n**3 * 2*2)/1e9,
+ op_label="GFlops",
+ parameters={"K": K})
+
+
+
+
+if __name__ == "__main__":
+ import sys
+ if len(sys.argv) > 1:
+ exec(sys.argv[1])
+ else:
+ from py.test.cmdline import main
+ main([__file__])
--
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