ACL-lowp

The project is designed to support efficient low precision computations on arm mobile devices.

It is implemented by utilizing SIMD MAC instructions of NEON for low precision data.

This library is not a typical GEMM but a GEMM library of bit-packed low precision data.

Currently, general matrix multiplication(GEMM) code in src directory is for 4 bit data.

References

This project is implemented based on arm compute library

• arm compute library https://github.com/ARM-software/ComputeLibrary

Prerequisites

• Scons

Building

Build the arm computer library with scons.

Build command depends on the target architecture and the OS of the compilation environment.

For example, if the target architecture is armv7a and the compilation environment is linux, the command is

scons asserts=1 neon=1 examples=1 os=linux arch=armv7a

Running the tests

There is example code executing low precision gemm

examples/neon_lowgemm.cpp

You can compile and run this by doing:

g++ examples/neon_lowgemm.cpp build/utils/*.o -O2 -std=c++11 -I. -Iinclude -Lbuild -larm_compute -larm_compute_core -larm_compute_graph -o neon_lowgemm

LD_LIBRARY_PATH=build/ ./neon_lowgemm

You can easily modify the example code and make your own.

Example kernel files

There are kernel files for serveral data types and operations.

If you want to compute with specific kernel file, simply move src file and build again.

For example:

mv kernel_examples/NEGEMMLowpMatrixMultiplyKernel_4bit.cpp src/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.cpp

Example result

Example result per precision latency on odroid-xu4.

GEMM is GEMM operation time, O/H is quantization overhead.