If the GEP instructions give us enough insights, model scalar accesses as
multi-dimensional (and generate the relevant run-time checks to ensure
correctness). This will allow us to simplify the dependence computation in
a subsequent commit.
llvm-svn: 247906
As specified in PR23888, run-time alias check generation is expensive
in terms of compile-time. This reduces the compile time by computing
minimal/maximal access only once for each base pointer
Contributed-by: Pratik Bhatu <cs12b1010@iith.ac.in>
llvm-svn: 243024
isl recently introduced a new interface to create run-time checks from
constraint sets. Use this interface to simplify our run-time check generation.
llvm-svn: 230640
Scops that only read seem generally uninteresting and scops that only write are
most likely initializations where there is also little to optimize. To not
waste compile time we bail early.
Differential Revision: http://reviews.llvm.org/D7735
llvm-svn: 229820
This allows us to skip ast and code generation if we did not optimize
a SCoP and will not generate parallel or alias annotations. The
initial heuristic to exit is simple but allows improvements later on.
All failing test cases have been modified to disable early exit, thus
to keep their coverage.
Differential Revision: http://reviews.llvm.org/D7254
llvm-svn: 228851
In case a GEP instruction references into a fixed size array e.g., an access
A[i][j] into an array A[100x100], LLVM-IR does not guarantee that the subscripts
always compute values that are within array bounds. We now derive the set of
parameter values for which all accesses are within bounds and add the assumption
that the scop is only every executed with this set of parameter values.
Example:
void foo(float A[][20], long n, long m {
for (long i = 0; i < n; i++)
for (long j = 0; j < m; j++)
A[i][j] = ...
This loop yields out-of-bound accesses if m is at least 20 and at the same time
at least one iteration of the outer loop is executed. Hence, we assume:
n <= 0 or m <= 20.
Doing so simplifies the dependence analysis problem, allows us to perform
more optimizations and generate better code.
TODO: The location where the GEP instruction is executed is not necessarily the
location where the memory is actually accessed. As a result scanning for GEP[s]
is imprecise. Even though this is not a correctness problem, this imprecision
may result in missed optimizations or non-optimal run-time checks.
In polybench where this mismatch between parametric loop bounds and fixed size
arrays is common, we see with this patch significant reductions in compile time
(up to 50%) and execution time (up to 70%). We see two significant compile time
regressions (fdtd-2d, jacobi-2d-imper), and one execution time regression
(trmm). Both regressions arise due to additional optimizations that have been
enabled by this patch. They can be addressed in subsequent commits.
http://reviews.llvm.org/D6369
llvm-svn: 222754
Tobias Grosser