:local:
LLVM has two vectorizers: The :ref:`Loop Vectorizer <loop-vectorizer>`,
-which operates on Loops, and the :ref:`Basic Block Vectorizer
-<bb-vectorizer>`, which optimizes straight-line code. These vectorizers
+which operates on Loops, and the :ref:`SLP Vectorizer
+<slp-vectorizer>`. These vectorizers
focus on different optimization opportunities and use different techniques.
-The BB vectorizer merges multiple scalars that are found in the code into
-vectors while the Loop Vectorizer widens instructions in the original loop
-to operate on multiple consecutive loop iterations.
+The SLP vectorizer merges multiple scalars that are found in the code into
+vectors while the Loop Vectorizer widens instructions in loops
+to operate on multiple consecutive iterations.
.. _loop-vectorizer:
-----
LLVM's Loop Vectorizer is now enabled by default for -O3.
+We plan to enable parts of the Loop Vectorizer on -O2 and -Os in future releases.
The vectorizer can be disabled using the command line:
.. code-block:: console
.. image:: linpack-pc.png
-.. _bb-vectorizer:
+.. _slp-vectorizer:
-The Basic Block Vectorizer
-==========================
-
-Usage
-------
-
-The Basic Block Vectorizer is not enabled by default, but it can be enabled
-through clang using the command line flag:
-
-.. code-block:: console
-
- $ clang -fslp-vectorize file.c
+The SLP Vectorizer
+==================
Details
-------
-The goal of basic-block vectorization (a.k.a. superword-level parallelism) is
-to combine similar independent instructions within simple control-flow regions
-into vector instructions. Memory accesses, arithemetic operations, comparison
-operations and some math functions can all be vectorized using this technique
-(subject to the capabilities of the target architecture).
+The goal of SLP vectorization (a.k.a. superword-level parallelism) is
+to combine similar independent instructions
+into vector instructions. Memory accesses, arithmetic operations, comparison
+operations, PHI-nodes, can all be vectorized using this technique.
For example, the following function performs very similar operations on its
inputs (a1, b1) and (a2, b2). The basic-block vectorizer may combine these
.. code-block:: c++
- int foo(int a1, int a2, int b1, int b2) {
- int r1 = a1*(a1 + b1)/b1 + 50*b1/a1;
- int r2 = a2*(a2 + b2)/b2 + 50*b2/a2;
- return r1 + r2;
+ void foo(int a1, int a2, int b1, int b2, int *A) {
+ A[0] = a1*(a1 + b1)/b1 + 50*b1/a1;
+ A[1] = a2*(a2 + b2)/b2 + 50*b2/a2;
}
+The SLP-vectorizer processes the code bottom-up, across basic blocks, in search of scalars to combine.
+
+Usage
+------
+
+The SLP Vectorizer is not enabled by default, but it can be enabled
+through clang using the command line flag:
+
+.. code-block:: console
+
+ $ clang -fslp-vectorize file.c
+
+LLVM has a second basic block vectorization phase
+which is more compile-time intensive (The BB vectorizer). This optimization
+can be enabled through clang using the command line flag:
+
+.. code-block:: console
+
+ $ clang -fslp-vectorize-aggressive file.c
+
+
+The SLP vectorizer is in early development stages but can already vectorize
+and accelerate many programs in the LLVM test suite.
+
+======================= ============
+Benchmark Name Gain
+======================= ============
+Misc/flops-7 -32.70%
+Misc/matmul_f64_4x4 -23.23%
+Olden/power -21.45%
+Misc/flops-4 -14.90%
+ASC_Sequoia/AMGmk -13.85%
+TSVC/LoopRerolling-flt -11.76%
+Misc/flops-6 -9.70%
+Misc/flops-5 -8.54%
+Misc/flops -8.12%
+TSVC/NodeSplitting-dbl -6.96%
+Misc-C++/sphereflake -6.74%
+Ptrdist/yacr2 -6.31%
+======================= ============