e2ccc3fb33
LLVM-IR names are commonly available in debug builds, but often not in release
builds. Hence, using LLVM-IR names to identify statements or memory reference
results makes the behavior of Polly depend on the compile mode. This is
undesirable. Hence, we now just number the statements instead of using LLVM-IR
names to identify them (this issue has previously been brought up by Zino
Benaissa).
However, as LLVM-IR names help in making test cases more readable, we add an
option '-polly-use-llvm-names' to still use LLVM-IR names. This flag is by
default set in the polly tests to make test cases more readable.
This change reduces the time in ScopInfo from 32 seconds to 2 seconds for the
following test case provided by Eli Friedman <efriedma@codeaurora.org> (already
used in one of the previous commits):
struct X { int x; };
void a();
#define SIG (int x, X **y, X **z)
typedef void (*fn)SIG;
#define FN { for (int i = 0; i < x; ++i) { (*y)[i].x += (*z)[i].x; } a(); }
#define FN5 FN FN FN FN FN
#define FN25 FN5 FN5 FN5 FN5
#define FN125 FN25 FN25 FN25 FN25 FN25
#define FN250 FN125 FN125
#define FN1250 FN250 FN250 FN250 FN250 FN250
void x SIG { FN1250 }
For a larger benchmark I have on-hand (10000 loops), this reduces the time for
running -polly-scops from 5 minutes to 4 minutes, a reduction by 20%.
The reason for this large speedup is that our previous use of printAsOperand
had a quadratic cost, as for each printed and unnamed operand the full function
was scanned to find the instruction number that identifies the operand.
We do not need to adjust the way memory reference ids are constructured, as
they do not use LLVM values.
Reviewed by: efriedma
Tags: #polly
Differential Revision: https://reviews.llvm.org/D32789
llvm-svn: 302072
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| cmake | ||
| docs | ||
| include/polly | ||
| lib | ||
| test | ||
| tools | ||
| unittests | ||
| utils | ||
| www | ||
| .arcconfig | ||
| .arclint | ||
| .gitattributes | ||
| .gitignore | ||
| CMakeLists.txt | ||
| CREDITS.txt | ||
| LICENSE.txt | ||
| README | ||
README
Polly - Polyhedral optimizations for LLVM ----------------------------------------- http://polly.llvm.org/ Polly uses a mathematical representation, the polyhedral model, to represent and transform loops and other control flow structures. Using an abstract representation it is possible to reason about transformations in a more general way and to use highly optimized linear programming libraries to figure out the optimal loop structure. These transformations can be used to do constant propagation through arrays, remove dead loop iterations, optimize loops for cache locality, optimize arrays, apply advanced automatic parallelization, drive vectorization, or they can be used to do software pipelining.