Julia fully supports ARMv8 (AArch64) processors, and supports ARMv7 and ARMv6 (AArch32) with some caveats. This file provides general guidelines for compilation, in addition to instructions for specific devices.
A list of known issues for ARM is available. If you encounter difficulties, please create an issue including the output from
32-bit (ARMv6, ARMv7)
Julia has been successfully compiled on several variants of the following ARMv6 & ARMv7 devices:
- ARMv7 / Cortex A15 Samsung Chromebooks running Ubuntu Linux under Crouton;
- Raspberry Pi.
Julia requires at least the
vfpv2 instruction sets. It's recommended to use
armv5 or soft float are not supported.
Raspberry Pi 1 / Raspberry Pi Zero
If the type of ARM CPU used in the Raspberry Pi is not detected by LLVM, then explicitly set the CPU target by adding the following to
To complete the build, you may need to increase the swap file size. To do so, edit
/etc/dphys-swapfile, changing the line:
before restarting the swapfile service:
sudo /etc/init.d/dphys-swapfile stop sudo /etc/init.d/dphys-swapfile start
Raspberry Pi 2
The type of ARM CPU used in the Raspberry Pi 2 is not detected by LLVM. Explicitly set the CPU target by adding the following to
Depending on the exact compiler and distribution, there might be a build failure due to unsupported inline assembly. In that case, add
Julia has been successfully built on the following ARMv8 devices:
ARMv8-A requires that
Make.user is configured as follows:
nVidia Jetson TX2
Julia builds and runs on the nVidia Jetson TX2 platform with minimal configuration changes.
Make.user as per the
AArch64 instructions in this document, follow the general build instructions. The majority of the build dependencies specified in the instructions are installed by the default configuration flashed by Jetpack 3.0. The remaining tools can be installed by issuing the following command:
sudo apt-get install gfortran wget cmake
A full parallel build, including LLVM, will complete in around two hours. All tests pass and CUDA functionality is available through, e.g., CUDAdrv.