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https://github.com/google/gemmlowp

Low-precision matrix multiplication
https://github.com/google/gemmlowp

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Low-precision matrix multiplication

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# gemmlowp: a small self-contained low-precision GEMM library



[![Build Status](https://secure.travis-ci.org/google/gemmlowp.png)](http://travis-ci.org/google/gemmlowp)



This is not a full linear algebra library, only a GEMM library: it only does

general matrix multiplication ("GEMM").



The meaning of "low precision" is detailed in this document:

[doc/low-precision.md](doc/low-precision.md)



Some of the general design is explained in [doc/design.md](doc/design.md).



**Warning:** This library goes very slow if compiled incorrectly; see below.



## Disclaimer



This is not an official Google product (experimental or otherwise), it is just

code that happens to be owned by Google.



## Mailing list



gemmlowp-related discussion, about either development or usage, is welcome on

this Google Group (mailing list / forum):



https://groups.google.com/forum/#!forum/gemmlowp



## Portability, target platforms/architectures



Should be portable to any platform with some C++11 and POSIX support, while we

have optional optimized code paths for specific architectures.



Required:



*   C++11 (a small conservative subset of it)



Required for some features:



*   Some POSIX interfaces:

    *   pthreads (for multi-threaded operation and for profiling).

    *   sysconf (for multi-threaded operation to detect number of cores; may be

        bypassed).



Optional:



*   Architecture-specific code paths use intrinsics or inline assembly. See

    "Architecture-specific optimized code paths" below.



## Architecture-specific optimized code paths



We have some optimized code paths for specific instruction sets. Some are

written in inline assembly, some are written in C++ using intrinsics. Both GCC

and Clang are supported.



Current optimized code paths:



*   ARM with NEON (both 32bit and 64bit).

*   Intel x86 with SSE 4.1 (both 32bit and 64bit).



When building for x86, it's very important to pass `-msse4.1` to the compiler,

otherwise gemmlowp will use slow reference code. Bazel users can compile by

running `bazel build --copt=-msse4.1 //gemmlowp:all`. The compiled binary should

work on all Intel CPUs since 2008 (including low power microarchitectures) as

well as AMD CPUs since 2011.



Please note when compiling binaries that don't need to be distributed, it's

generally a better idea to pass `-march=native` to the compiler. That flag

implies `-msse4.1` flag, along with others that might be helpful. This of course

assumes the host machine supports those instructions. Bazel users should prefer

to run `bazel build --config=opt //gemmlowp:all` instead.



Details of what it takes to make an efficient port of gemmlowp, namely writing a

suitable GEMM kernel and accompanying packing code, are explained in this file:

[doc/kernel.md](doc/kernel.md).



## Public interfaces



### The gemmlowp public interface



gemmlowp's main public interface is in the `public/` subdirectory.



This is a headers-only library, so there is nothing to link to.



Usage documentation, and comments on the deprecation status of each public entry

point, may be found in [doc/public.md](doc/public.md) .



A full, self-contained usage example, showing how to quantize float matrices and

perform a quantized matrix multiplication approximating a float matrix

multiplication, is given in

[doc/quantization_example.cc](doc/quantization_example.cc).



### Old EightBitIntGemm legacy deprecated interface



The `eight_bit_int_gemm/` subdirectory contains an alternate interface that

should be considered purely legacy, deprecated, and going to be removed at some

point in the future.



## Building



### Building by manually invoking your compiler



Because gemmlowp is so simple, working with it involves only single-command-line

compiler invocations. Therefore we expect that most people working with gemmlowp

will either manually invoke their compiler, or write their own rules for their

own preferred build system.



Keep in mind (previous section) that gemmlowp itself is a pure-headers-only

library so there is nothing to build.



For a Android gemmlowp development workflow, the `scripts/` directory contains a

script to build and run a program on an Android device:



```

scripts/test-android.sh

```



### Building using Bazel



That being said, we also maintain a Bazel BUILD system as part of gemmlowp. Its

usage is not mandatory at all and is only one possible way that gemmlowp

libraries and tests may be built. If you are interested, Bazel's home page is

http://bazel.build/ And you can get started with using Bazel to build gemmlowp

targets by first creating an empty WORKSPACE file in a parent directory, for

instance:



```

$ cd gemmlowp/..  # change to parent directory containing gemmlowp/

$ touch WORKSPACE # declare that to be our workspace root

$ bazel build gemmlowp:all

```



### Building gemmlowp - Using vcpkg



You can download and install gemmlowp using the [vcpkg](https://github.com/Microsoft/vcpkg) dependency manager:



    git clone https://github.com/Microsoft/vcpkg.git

    cd vcpkg

    ./bootstrap-vcpkg.sh

    ./vcpkg integrate install

    ./vcpkg install gemmlowp



The gemmlowp port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please [create an issue or pull request](https://github.com/Microsoft/vcpkg) on the vcpkg repository.



## Testing



### Testing by manually building and running tests



The test/ directory contains unit tests. The primary unit test is



```

test/test.cc

```



Since it covers also the EightBitIntGemm interface, it needs to be linked

against



```

eight_bit_int_gemm/eight_bit_int_gemm.cc

```



It also uses realistic data captured from a neural network run in



```

test/test_data.cc

```



Thus you'll want to pass the following list of source files to your

compiler/linker:



```

test/test.cc

eight_bit_int_gemm/eight_bit_int_gemm.cc

test/test_data.cc

```



The `scripts/` directory contains a script to build and run a program on an

Android device:



```

scripts/test-android.sh

```



It expects the `CXX` environment variable to point to an Android toolchain's C++

compiler, and expects source files (and optionally, cflags) as command-line

parameters. To build and run the above-mentioned main unit test, first set `CXX`

e.g.:



```

$ export CXX=/some/toolchains/arm-linux-androideabi-4.8/bin/arm-linux-androideabi-g++

```



Then run:



```

$ ./scripts/test-android.sh \

test/test.cc \

eight_bit_int_gemm/eight_bit_int_gemm.cc \

test/test_data.cc

```



### Testing using Bazel



Alternatively, you can use Bazel to build and run tests. See the Bazel

instruction in the above section on building. Once your Bazel workspace is set

up, you can for instance do:



```

$ bazel test gemmlowp:all

```



## Troubleshooting Compilation



If you're having trouble finding the compiler, follow these instructions to

build a standalone toolchain:

https://developer.android.com/ndk/guides/standalone_toolchain.html



Here's an example of setting up Clang 3.5:



```

$ export INSTALL_DIR=~/toolchains/clang-21-stl-gnu

$ $NDK/build/tools/make-standalone-toolchain.sh \

--toolchain=arm-linux-androideabi-clang3.5 --platform=android-21 \

--install-dir=$INSTALL_DIR

$ export CXX="$INSTALL_DIR/bin/arm-linux-androideabi-g++ \

--sysroot=$INSTALL_DIR/sysroot"

```



Some compilers (e.g. the default clang++ in the same bin directory) don't

support NEON assembly. The benchmark build process will issue a warning if

support isn't detected, and you should make sure you're using a compiler like

arm-linux-androideabi-g++ that does include NEON.



## Benchmarking



The main benchmark is



```

test/benchmark.cc

```



It doesn't need to be linked to any other source file. We recommend building

with assertions disabled (`-DNDEBUG`).



For example, the benchmark can be built and run on an Android device by doing:



```

$ ./scripts/test-android.sh test/benchmark.cc -DNDEBUG

```



If `GEMMLOWP_TEST_PROFILE` is defined then the benchmark will be built with

profiling instrumentation (which makes it slower) and will dump profiles. See

next section on profiling.



## Profiling



The `profiling/` subdirectory offers a very simple, naive, inaccurate,

non-interrupting sampling profiler that only requires pthreads (no signals).



It relies on source code being instrumented with pseudo-stack labels. See

`profiling/instrumentation.h`. A full example of using this profiler is given in

the top comment of `profiling/profiler.h`.



## Contributing



Contribution-related discussion is always welcome on the gemmlowp mailing list

(see above).



We try to keep a current list of TODO items in the `todo/` directory.

Prospective contributors are welcome to pick one to work on, and communicate

about it on the gemmlowp mailing list.



Details of the contributing process, including legalese, are in CONTRIBUTING.



## Performance goals



Our performance goals differ from typical GEMM performance goals in the

following ways:



1.  We care not only about speed, but also about minimizing power usage. We

    specifically care about charge usage in mobile/embedded devices. This

    implies that we care doubly about minimizing memory bandwidth usage: we care

    about it, like any GEMM, because of the impact on speed, and we also care

    about it because it is a key factor of power usage.



2.  Most GEMMs are optimized primarily for large dense matrix sizes (>= 1000).

    We do care about large sizes, but we also care specifically about the

    typically smaller matrix sizes encountered in various mobile applications.

    This means that we have to optimize for all sizes, not just for large enough

    sizes.