From 9ad444e66a04108f560b8f6cf39691385bb5dc2c Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Fri, 11 Nov 2011 12:42:09 -0500
Subject: [PATCH] Pick (more) sensible names for reduction inames. Remove
non-ND FEM quadrature.
---
loopy/preprocess.py | 2 +-
test/test_fem_assembly.py | 82 ---------------------------------------
2 files changed, 1 insertion(+), 83 deletions(-)
diff --git a/loopy/preprocess.py b/loopy/preprocess.py
index fec2f3e80..59ac1fc05 100644
--- a/loopy/preprocess.py
+++ b/loopy/preprocess.py
@@ -141,7 +141,7 @@ def realize_reduction(kernel):
from pymbolic import var
- target_var_name = kernel.make_unique_var_name("acc",
+ target_var_name = kernel.make_unique_var_name("acc_"+"_".join(expr.inames),
extra_used_vars=set(new_temporary_variables))
target_var = var(target_var_name)
diff --git a/test/test_fem_assembly.py b/test/test_fem_assembly.py
index bae8fcdca..136fccfbc 100644
--- a/test/test_fem_assembly.py
+++ b/test/test_fem_assembly.py
@@ -26,88 +26,6 @@ def test_laplacian_stiffness(ctx_factory):
from pymbolic import var
Nc_sym = var("Nc")
- knl = lp.make_kernel(ctx.devices[0],
- "[Nc] -> {[K,i,j,q, ax_a, ax_b, ax_c]: 0<=K<Nc and 0<=i,j<%(Nb)d and 0<=q<%(Nq)d "
- "and 0<= ax_c < %(dim)d}"
- % dict(Nb=Nb, Nq=Nq, dim=dim),
- [
- "dPsi(a, dxi) := sum_float32(ax_c,"
- " jacInv[ax_c,dxi,K,q] * DPsi[ax_c,a,q])",
- "A[K, i, j] = sum_float32(q, w[q] * jacDet[K,q] * ("
- "dPsi(0,0)*dPsi(1,0) + dPsi(0,1)*dPsi(1,1)))"
- ],
- [
- lp.ArrayArg("jacInv", dtype, shape=(dim, dim, Nc_sym, Nq), order=order),
- lp.ConstantArrayArg("DPsi", dtype, shape=(dim, Nb, Nq), order=order),
- lp.ArrayArg("jacDet", dtype, shape=(Nc_sym, Nq), order=order),
- lp.ConstantArrayArg("w", dtype, shape=(Nq, dim), order=order),
- lp.ArrayArg("A", dtype, shape=(Nc_sym, Nb, Nb), order=order),
- lp.ScalarArg("Nc", np.int32, approximately=1000),
- ],
- name="lapquad", assumptions="Nc>=1")
-
- knl = lp.tag_dimensions(knl, dict(ax_c="unr"))
- seq_knl = knl
- #print lp.preprocess_kernel(seq_knl)
- #1/0
-
- def variant_1(knl):
- # no ILP across elements
- knl = lp.split_dimension(knl, "K", 16, outer_tag="g.0", slabs=(0,1))
- knl = lp.tag_dimensions(knl, {"i": "l.0", "j": "l.1"})
- knl = lp.add_prefetch(knl, 'jacInv',
- ["jacInv_dim_0", "jacInv_dim_1", "K_inner", "q"])
- return knl
-
- def variant_2(knl):
- # with ILP across elements
- knl = lp.split_dimension(knl, "K", 16, outer_tag="g.0", slabs=(0,1))
- knl = lp.split_dimension(knl, "K_inner", 4, inner_tag="ilp")
- knl = lp.tag_dimensions(knl, {"i": "l.0", "j": "l.1"})
- knl = lp.add_prefetch(knl, "jacInv",
- ["jacInv_dim_0", "jacInv_dim_1", "K_inner_inner", "K_inner_outer", "q"])
- return knl
-
- def variant_3(knl):
- # no ILP across elements, precompute dPsiTransf
- knl = lp.split_dimension(knl, "K", 16, outer_tag="g.0", slabs=(0,1))
- knl = lp.tag_dimensions(knl, {"i": "l.0", "j": "l.1"})
- knl = lp.precompute(knl, "dPsi", np.float32,)
- #default_tag=None)
- knl = lp.add_prefetch(knl, "jacInv",
- ["jacInv_dim_0", "jacInv_dim_1", "K_inner", "q"])
- return knl
-
- #for variant in [variant_1, variant_2]:
- for variant in [variant_3]:
- kernel_gen = lp.generate_loop_schedules(variant(knl),
- loop_priority=["jacInv_dim_0", "jacInv_dim_1"])
- kernel_gen = lp.check_kernels(kernel_gen, dict(Nc=Nc))
-
- lp.auto_test_vs_seq(seq_knl, ctx, kernel_gen,
- op_count=0, op_label="GFlops",
- parameters={"Nc": Nc}, print_seq_code=True,
- timing_rounds=30)
-
-
-
-
-def test_laplacian_stiffness_nd(ctx_factory):
- dtype = np.float32
- ctx = ctx_factory()
- order = "C"
-
- dim = 2
-
- Nq = 40 # num. quadrature points
- Nc = 1000 # num. cells
- Nb = 20 # num. basis functions
-
- # K - run-time symbolic
-
- from pymbolic import var
- Nc_sym = var("Nc")
-
knl = lp.make_kernel(ctx.devices[0],
"[Nc] -> {[K,i,j,q, ax_a, ax_b]: 0<=K<Nc and 0<=i,j<%(Nb)d and 0<=q<%(Nq)d "
"and 0<= ax_a, ax_b < %(dim)d}"
--
GitLab