From ee8ce79cc952fe5743b70176e72e5e86c69014d0 Mon Sep 17 00:00:00 2001
From: Dominic Kempf <dominic.kempf@iwr.uni-heidelberg.de>
Date: Thu, 30 Mar 2017 15:14:09 +0200
Subject: [PATCH] Move permutation code to its own module
---
python/dune/perftool/sumfact/permutation.py | 86 +++++++++++++++++++++
python/dune/perftool/sumfact/sumfact.py | 83 +-------------------
2 files changed, 90 insertions(+), 79 deletions(-)
create mode 100644 python/dune/perftool/sumfact/permutation.py
diff --git a/python/dune/perftool/sumfact/permutation.py b/python/dune/perftool/sumfact/permutation.py
new file mode 100644
index 00000000..34d32298
--- /dev/null
+++ b/python/dune/perftool/sumfact/permutation.py
@@ -0,0 +1,86 @@
+""" Permute sum factorization kernels """
+
+# TODO!
+# * get rid of the underscores in names
+# * Pass the entire kernel object into the strategy thing
+
+import itertools
+
+
+def _sf_permutation_heuristic(permutations, stage):
+ """Heuristic to choose a permutation
+
+ - Stage 1: Pick the permutation where in permutations[1:] most
+ elements are ordered by size
+ - Stage 3: Pick the permutation where in permutations[:-1] most
+ elements are ordered by size
+ """
+ def cost(perm, stage):
+ cost = 0
+ for i in range(0, len(perm) - 2):
+ if stage == 1:
+ if perm[i + 1] > perm[i + 2]:
+ cost += 1
+ if stage == 3:
+ if perm[0] > perm[i + 1]:
+ cost += 1
+ return cost
+
+ perm = min(permutations, key=lambda i: cost(i, stage))
+ return perm
+
+
+def _sf_flop_cost(a_matrices):
+ """Computational cost of sumfactorization with this list of a_matrices
+ """
+ cost = 0
+ for l in range(len(a_matrices)):
+ cost_m = 1
+ cost_n = 1
+ for i in range(l + 1):
+ cost_m *= a_matrices[i].rows
+ for i in range(l, len(a_matrices)):
+ cost_n *= a_matrices[i].cols
+ cost += cost_m * cost_n
+ return cost
+
+
+def _sf_permutation_strategy(a_matrices, stage):
+ """Choose permutation of a_matrices list based on computational cost
+
+ Note: If there are multiple permutations with the same cost a
+ heuristic is used to pick one.
+ """
+ # Combine permutation and a_matrices list
+ perm = [i for i, _ in enumerate(a_matrices)]
+ perm_a_matrices = zip(perm, a_matrices)
+
+ # Find cost for all possible permutations of a_matrices list
+ perm_cost = []
+ for permutation in itertools.permutations(perm_a_matrices):
+ perm, series = zip(*permutation)
+ cost = _sf_flop_cost(series)
+ perm_cost.append((perm, cost))
+
+ # Find minimal cost and all permutations with that cost
+ _, costs = zip(*perm_cost)
+ minimal_cost = min(costs)
+ minimal_cost_permutations = [p[0] for p in perm_cost if p[1] == minimal_cost]
+
+ # Use heuristic to pic one of the minimal cost permutations
+ perm = _sf_permutation_heuristic(minimal_cost_permutations, stage)
+ return perm
+
+
+def _permute_forward(t, perm):
+ tmp = []
+ for pos in perm:
+ tmp.append(t[pos])
+ return tuple(tmp)
+
+
+def _permute_backward(t, perm):
+ tmp = [None] * len(t)
+ for i, pos in enumerate(perm):
+ tmp[pos] = t[i]
+ return tuple(tmp)
\ No newline at end of file
diff --git a/python/dune/perftool/sumfact/sumfact.py b/python/dune/perftool/sumfact/sumfact.py
index 95fceb08..2500a69d 100644
--- a/python/dune/perftool/sumfact/sumfact.py
+++ b/python/dune/perftool/sumfact/sumfact.py
@@ -64,6 +64,10 @@ from pymbolic.primitives import (Call,
from dune.perftool.sumfact.quadrature import quadrature_inames
from dune.perftool.sumfact.vectorization import find_sumfact
from loopy.symbolic import FunctionIdentifier, IdentityMapper
+from dune.perftool.sumfact.permutation import (_sf_permutation_strategy,
+ _permute_backward,
+ _permute_forward,
+ )
import loopy as lp
import numpy as np
@@ -360,85 +364,6 @@ def generate_accumulation_instruction(visitor, accterm, measure, subdomain_id):
insn_dep = emit_sumfact_kernel(None, restriction, insn_dep)
-def _sf_permutation_heuristic(permutations, stage):
- """Heuristic to choose a permutation
-
- - Stage 1: Pick the permutation where in permutations[1:] most
- elements are ordered by size
- - Stage 3: Pick the permutation where in permutations[:-1] most
- elements are ordered by size
- """
- def cost(perm, stage):
- cost = 0
- for i in range(0, len(perm) - 2):
- if stage == 1:
- if perm[i + 1] > perm[i + 2]:
- cost += 1
- if stage == 3:
- if perm[0] > perm[i + 1]:
- cost += 1
- return cost
-
- perm = min(permutations, key=lambda i: cost(i, stage))
- return perm
-
-
-def _sf_flop_cost(a_matrices):
- """Computational cost of sumfactorization with this list of a_matrices
- """
- cost = 0
- for l in range(len(a_matrices)):
- cost_m = 1
- cost_n = 1
- for i in range(l + 1):
- cost_m *= a_matrices[i].rows
- for i in range(l, len(a_matrices)):
- cost_n *= a_matrices[i].cols
- cost += cost_m * cost_n
- return cost
-
-
-def _sf_permutation_strategy(a_matrices, stage):
- """Choose permutation of a_matrices list based on computational cost
-
- Note: If there are multiple permutations with the same cost a
- heuristic is used to pick one.
- """
- # Combine permutation and a_matrices list
- perm = [i for i, _ in enumerate(a_matrices)]
- perm_a_matrices = zip(perm, a_matrices)
-
- # Find cost for all possible permutations of a_matrices list
- perm_cost = []
- for permutation in itertools.permutations(perm_a_matrices):
- perm, series = zip(*permutation)
- cost = _sf_flop_cost(series)
- perm_cost.append((perm, cost))
-
- # Find minimal cost and all permutations with that cost
- _, costs = zip(*perm_cost)
- minimal_cost = min(costs)
- minimal_cost_permutations = [p[0] for p in perm_cost if p[1] == minimal_cost]
-
- # Use heuristic to pic one of the minimal cost permutations
- perm = _sf_permutation_heuristic(minimal_cost_permutations, stage)
- return perm
-
-
-def _permute_forward(t, perm):
- tmp = []
- for pos in perm:
- tmp.append(t[pos])
- return tuple(tmp)
-
-
-def _permute_backward(t, perm):
- tmp = [None] * len(t)
- for i, pos in enumerate(perm):
- tmp[pos] = t[i]
- return tuple(tmp)
-
-
@generator_factory(item_tags=("sumfactkernel",), context_tags=("kernel",), cache_key_generator=lambda a, b, s, **kw: (a, b, s, kw.get("restriction", 0)))
def sum_factorization_kernel(a_matrices,
buf,
--
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