disable ctest math_test due to SIGILL in clang7 debug builder

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  1. .github/
  2. debian/
  3. g3doc/
  4. hwy/
  5. BUILD
  6. CMakeLists.txt
  7. CMakeLists.txt.in
  8. CONTRIBUTING
  9. libhwy-contrib.pc.in
  10. libhwy-test.pc.in
  11. libhwy.pc.in
  12. LICENSE
  13. README.md
  14. run_tests.bat
  15. run_tests.sh
  16. WORKSPACE
README.md

Efficient and performance-portable SIMD

Highway is a C++ library for SIMD (Single Instruction, Multiple Data), i.e. applying the same operation to multiple ‘lanes’ using a single CPU instruction.

Why Highway?

  • more portable (same source code) than platform-specific intrinsics,
  • works on a wider range of compilers than compiler-specific vector extensions,
  • more dependable than autovectorization,
  • easier to write/maintain than assembly language,
  • supports runtime dispatch,
  • supports variable-length vector architectures.

Current status

Supported targets: scalar, S-SSE3, SSE4, AVX2, AVX-512, AVX3_DL (~Icelake, requires opt-in by defining HWY_WANT_AVX3_DL), NEON (ARMv7 and v8), SVE, WASM SIMD.

SVE is tested using farm_sve (see acknowledgments). SVE2 is implemented but not yet validated. A subset of RVV is implemented and tested with GCC and QEMU. Work is underway to compile using LLVM, which has different intrinsics with AVL.

Version 0.11 is considered stable enough to use in other projects, and is expected to remain backwards compatible unless serious issues are discovered while finishing the RVV target. After that, Highway will reach version 1.0.

Continuous integration tests build with a recent version of Clang (running on x86 and QEMU for ARM) and MSVC from VS2015 (running on x86).

Before releases, we also test on x86 with Clang and GCC, and ARMv7/8 via GCC cross-compile and QEMU. See the testing process for details.

The contrib directory contains SIMD-related utilities: an image class with aligned rows, and a math library (16 functions already implemented, mostly trigonometry).

Installation

This project uses cmake to generate and build. In a Debian-based system you can install it via:

sudo apt install cmake

Highway‘s unit tests use googletest. By default, Highway’s CMake downloads this dependency at configuration time. You can disable this by setting the HWY_SYSTEM_GTEST CMake variable to ON and installing gtest separately:

sudo apt install libgtest-dev

To build and test the library the standard cmake workflow can be used:

mkdir -p build && cd build
cmake ..
make -j && make test

Or you can run run_tests.sh (run_tests.bat on Windows).

Bazel is also supported for building, but it is not as widely used/tested.

Quick start

You can use the benchmark inside examples/ as a starting point.

A quick-reference page briefly lists all operations and their parameters, and the instruction_matrix indicates the number of instructions per operation.

We recommend using full SIMD vectors whenever possible for maximum performance portability. To obtain them, pass a HWY_FULL(float) tag to functions such as Zero/Set/Load. There is also the option of a vector of up to N (a power of two <= 16/sizeof(T)) lanes of type T: HWY_CAPPED(T, N). If HWY_TARGET == HWY_SCALAR, the vector always has one lane. For all other targets, up to 128-bit vectors are guaranteed to be available.

Functions using Highway must be inside namespace HWY_NAMESPACE { (possibly nested in one or more other namespaces defined by the project), and additionally either prefixed with HWY_ATTR, or residing between HWY_BEFORE_NAMESPACE() and HWY_AFTER_NAMESPACE().

  • For static dispatch, HWY_TARGET will be the best available target among HWY_BASELINE_TARGETS, i.e. those allowed for use by the compiler (see quick-reference). Functions inside HWY_NAMESPACE can be called using HWY_STATIC_DISPATCH(func)(args) within the same module they are defined in. You can call the function from other modules by wrapping it in a regular function and declaring the regular function in a header.

  • For dynamic dispatch, a table of function pointers is generated via the HWY_EXPORT macro that is used by HWY_DYNAMIC_DISPATCH(func)(args) to call the best function pointer for the current CPU's supported targets. A module is automatically compiled for each target in HWY_TARGETS (see quick-reference) if HWY_TARGET_INCLUDE is defined and foreach_target.h is included.

Compiler flags

Applications should be compiled with optimizations enabled - without inlining, SIMD code may slow down by factors of 10 to 100. For clang and GCC, -O2 is generally sufficient.

For MSVC, we recommend compiling with /Gv to allow non-inlined functions to pass vector arguments in registers. If intending to use the AVX2 target together with half-width vectors (e.g. for PromoteTo), it is also important to compile with /arch:AVX2. This seems to be the only way to generate VEX-encoded SSE4 instructions on MSVC. Otherwise, mixing VEX-encoded AVX2 instructions and non-VEX SSE4 may cause severe performance degradation. Unfortunately, the resulting binary will then require AVX2. Note that no such flag is needed for clang and GCC because they support target-specific attributes, which we use to ensure proper VEX code generation for AVX2 targets.

Strip-mining loops

To vectorize a loop, “strip-mining” transforms it into an outer loop and inner loop with number of iterations matching the preferred vector width.

In this section, let T denote the element type, d = HWY_FULL(T), count the number of elements to process, and N = Lanes(d) the number of lanes in a full vector. Assume the loop body is given as a function template<bool partial, class D> void LoopBody(D d, size_t max_n).

Highway offers several ways to express loops where N need not divide count:

  • Ensure all inputs/outputs are padded. Then the loop is simply

    for (size_t i = 0; i < count; i += N) LoopBody<false>(d, 0);
    

    Here, the template parameter and second function argument are not needed.

    This is the preferred option, unless N is in the thousands and vector operations are pipelined with long latencies. This was the case for supercomputers in the 90s, but nowadays ALUs are cheap and we see most implementations split vectors into 1, 2 or 4 parts, so there is little cost to processing entire vectors even if we do not need all their lanes. Indeed this avoids the (potentially large) cost of predication or partial loads/stores on older targets, and does not duplicate code.

  • Process whole vectors as above, followed by a scalar loop:

    size_t i = 0;
    for (; i + N <= count; i += N) LoopBody<false>(d, 0);
    for (; i < count; ++i) LoopBody<false>(HWY_CAPPED(T, 1)(), 0);
    

    The template parameter and second function arguments are again not needed.

    This avoids duplicating code, and is reasonable if count is large. If count is small, the second loop may be slower than the next option.

  • Process whole vectors as above, followed by a single call to a modified LoopBody with masking:

    size_t i = 0;
    for (; i + N <= count; i += N) {
      LoopBody<false>(d, 0);
    }
    if (i < count) {
      LoopBody<true>(d, count - i);
    }
    

    Now the template parameter and second function argument can be used inside LoopBody to ‘blend’ the new partial vector with previous memory contents: Store(IfThenElse(FirstN(d, N), partial, prev_full), d, aligned_pointer);.

    This is a good default when it is infeasible to ensure vectors are padded. In contrast to the scalar loop, only a single final iteration is needed.

Additional resources

Acknowledgments

We have used farm-sve by Berenger Bramas; it has proved useful for checking the SVE port on an x86 development machine.

This is not an officially supported Google product. Contact: janwas@google.com