abishekmuthian

When postgres was not compiled with systemd support, this start script will work.
Source: https://itectec.com/unixlinux/linux-systemd-postgresql-start-script/
/usr/lib/systemd/system/postgresql.service

abishekmuthian

<TaskerData sr="" dvi="1" tv="5.11.14">
	<Profile sr="prof28" ve="2">
		<cdate>1615003515868</cdate>
		<edate>1616131937187</edate>
		<flags>8</flags>
		<id>28</id>
		<mid0>27</mid0>
		<mid1>29</mid1>
		<nme>inshorts display</nme>
		<App sr="con0" ve="2">

abishekmuthian

abishekmuthian

This patch fixes ARM (aarch64) bazel build rules for boost libraries when
building ray as discussed in this issue - https://github.com/ray-project/ray/issues/7184.
Patch v2 by Abishek Muthian (@heavyinfo).
--- BUILD.boost	2020-02-23 09:03:02.937872389 +0530
+++ BUILD.boost	2020-02-26 07:18:26.287128627 +0530
@@ -49,6 +49,15 @@
 )
 
 config_setting(
+    name = "linux_aarch64",

abishekmuthian

Dependencies

Only dependencies which aren't highly likely to be featured in a ARM development environment are featured here, Obvious dependencies such as Python3, Python2, pip, wheel, GCC etc. aren't covered here.

Bazel

Note : Use bazel 1.x.x for Ray as 2.x.x is not supported.

sudo apt-get install build-essential openjdk-8-jdk unzip
export JAVA_HOME="/usr/bin/java"
wget https://github.com/bazelbuild/bazel/releases/download/1.0.0/bazel-1.0.0-dist.zip
unzip bazel-1.0.0-dist.zip

abishekmuthian

My setup

I'm using Nvidia Jetson nano.

Quad-core ARM® Cortex®-A57 MPCore processor

NVIDIA Maxwell™ architecture with 128 NVIDIA CUDA® cores

4 GB 64-bit LPDDR4 1600MHz - 25.6 GB/s

Ubuntu 18.04 LTS

abishekmuthian

#!/bin/bash

# This script will install pytorch, torchvision, torchtext and spacy on nano. 
# If you have any of these installed already on your machine, you can skip those.

sudo apt-get -y update
sudo apt-get -y upgrade
#Dependencies
sudo apt-get install python3-setuptools

abishekmuthian

Why build Apache Arrow from source on ARM?

Apache Arrow is an in-memory data structure used in several projects. It's python module can be used to save what's on the memory to the disk via python code, commonly used in the Machine Learning projects. With low RAM, ARM devices can make use of it but there seems to be an configuration error with the packaged binaries as of version 0.15.1 and so we're forced to build and install from the source.

The installation build steps are based on official guidelines but modified for ARM and has taken clues from building Ray for ARM.

My setup

I'm using Nvidia Jetson nano.

Quad-core ARM® Cortex®-A57 MPCore processor