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Scientific Python From Source

This document will walk you through compiling your own scientific python distribution from source, without sudo, on a linux machine. The core numpy and scipy libraries will be linked against Intel MKL for maximum performance.

This procedure has been tested with Rocks Cluster Linux 6.0 (Mamba) and CentOS 6.3.

Compiling Python From Source

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs

	# This script create a Centos Minimal Unattended ISO

	# This method is based on excellent article http://pyxlmap.net/technology/software/linux/custom-centos-iso
	#
	# This script has be tested with CentOS 7.2 (on the orign server) to install CentOS 7.2 (on the target server)
	# TODO:
	# * test package update to reduce the update task on the target system. The following command downloads all updates :
	# (cd $CENTOS_CUSTOM_PATH/Packages ; yumdownloader $(for i in ; { echo ${i%%-[0-9]}; } ) )

	# Some global settings :

-#!/bin/sh
-EXPECTED_ARGS=2
-E_BADARGS=65
-if [ $# -ne $EXPECTED_ARGS ]
-then
-  echo "Usage: `basename $0` {reservationname} {nodelist}"
-  exit $E_BADARGS
-fi