I would like to use lib-python and repl via graalvm on aarch64. If that isn’t possible I use Golang or C++ but hopefully that is possible solve.
In the past I used not the official way compile things via substratevm.. but changed lot of things..
to clarify, i had success with producing aarch64 binaries of clj-kondo and bb. the compilation succeeded on android via proot, but it also worked in a qemu aarch64 environment (-M virt). qemu building takes much longer -- in the case of bb it took 2 hours in qemu vs 20 mins on android.
iiuc, rpi 3 should be possible as well with an appropriate distribution, but iiuc memory is limited there.
may be that should be "should be possible to run binaries" -- building may be another story.
@sogaiu did you use java11? Yesterday for me on Ubuntu doesn’t work with official graalvm image :/ - before this I successfully compiled with substratevm/old way.
I added extra 4gb swap and I have 4gb. But didn’t finish within 3-4 hours. I try again..
Maybe qemu better idea..
not quite sure i follow -- what i used was: https://github.com/graalvm/graalvm-ce-builds/releases/download/vm-19.3.1/graalvm-ce-java11-linux-aarch64-19.3.1.tar.gz (so that's the aarch64 build for linux that is tied to java11)
for qemu, the following tutorial was very helpful: https://translatedcode.wordpress.com/2017/07/24/installing-debian-on-qemus-64-bit-arm-virt-board/
to get bb to work some changes were necessary -- those should be summarized here: https://github.com/borkdude/babashka/issues/241#issuecomment-6109082121🍻
assuming the tutorial is followed, my qemu invocation looked like this:
qemu-system-aarch64 \ -smp 4 \ -M virt \ -m 8192 \ -cpu cortex-a53 \ -kernel vmlinuz-4.9.0-12-arm64 \ -initrd initrd.img-4.9.0-12-arm64 \ -append 'root=/dev/vda3' \ -drive if=none,file=hda.raw,id=hd \ -device virtio-blk-pci,drive=hd \ -netdev user,id=mynet \ -device virtio-net-pci,netdev=mynet \ -nographic
vda3 part will obviously depend on how partitioning is done -- my value is different from what was in the tutorial
note that i allocated 8gb of memory1👍
...and 4 cores
-Xmx value in bb's build script seemed to help too
Thanks!! I check all things and redo now!! 👍
good luck 🙂
sbThat was slow really on jetson nano