llvm-project/mlir/test/lib/Dialect/Math/TestPolynomialApproximation.cpp
Emilio Cota 35553d452b [mlir] Add polynomial approximation for vectorized math::Rsqrt
This patch adds a polynomial approximation that matches the
approximation in Eigen.

Note that the approximation only applies to vectorized inputs;
the scalar rsqrt is left unmodified.

The approximation is protected with a flag since it emits an AVX2
intrinsic (generated via the X86Vector). This is the only reasonably
clean way that I could find to generate the exact approximation that
I wanted (i.e. an identical one to Eigen's).

I considered two alternatives:

1. Introduce a Rsqrt intrinsic in LLVM, which doesn't exist yet.
   I believe this is because there is no definition of Rsqrt that
   all backends could agree on, since hardware instructions that
   implement it have widely varying degrees of precision.
   This is something that the standard could mandate, but Rsqrt is
   not part of IEEE754, so I don't think this option is feasible.

2. Emit fdiv(1.0, sqrt) with fast math flags to allow reciprocal
   transformations. Although portable, this doesn't allow us
   to generate exactly the code we want; it is the LLVM backend,
   and not MLIR, who controls what code is generated based on the
   target CPU.

Reviewed By: ezhulenev

Differential Revision: https://reviews.llvm.org/D112192
2021-10-23 04:56:12 -07:00

68 lines
2.4 KiB
C++

//===- TestPolynomialApproximation.cpp - Test math ops approximations -----===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file contains test passes for expanding math operations into
// polynomial approximations.
//
//===----------------------------------------------------------------------===//
#include "mlir/Dialect/Arithmetic/IR/Arithmetic.h"
#include "mlir/Dialect/Math/IR/Math.h"
#include "mlir/Dialect/Math/Transforms/Passes.h"
#include "mlir/Dialect/Vector/VectorOps.h"
#include "mlir/Dialect/X86Vector/X86VectorDialect.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
using namespace mlir;
namespace {
struct TestMathPolynomialApproximationPass
: public PassWrapper<TestMathPolynomialApproximationPass, FunctionPass> {
TestMathPolynomialApproximationPass() = default;
TestMathPolynomialApproximationPass(
const TestMathPolynomialApproximationPass &pass) {}
void runOnFunction() override;
void getDependentDialects(DialectRegistry &registry) const override {
registry.insert<arith::ArithmeticDialect, math::MathDialect,
vector::VectorDialect>();
if (enableAvx2)
registry.insert<x86vector::X86VectorDialect>();
}
StringRef getArgument() const final {
return "test-math-polynomial-approximation";
}
StringRef getDescription() const final {
return "Test math polynomial approximations";
}
Option<bool> enableAvx2{
*this, "enable-avx2",
llvm::cl::desc("Enable approximations that emit AVX2 intrinsics via the "
"X86Vector dialect"),
llvm::cl::init(false)};
};
} // end anonymous namespace
void TestMathPolynomialApproximationPass::runOnFunction() {
RewritePatternSet patterns(&getContext());
MathPolynomialApproximationOptions approx_options;
approx_options.enableAvx2 = enableAvx2;
populateMathPolynomialApproximationPatterns(patterns, approx_options);
(void)applyPatternsAndFoldGreedily(getOperation(), std::move(patterns));
}
namespace mlir {
namespace test {
void registerTestMathPolynomialApproximationPass() {
PassRegistration<TestMathPolynomialApproximationPass>();
}
} // namespace test
} // namespace mlir