Rob robmsmt

## gcp-start-iap-tunnel-ssh-proxy-magic.sh
#!/usr/bin/env bash
# ~/.ssh/gcp-start-iap-tunnel-ssh-proxy-magic.sh
# a script to be used as SSH ProxyCommand to allow fully functional SSH access to any Google Cloud Compute Engine VMs allowing IAP access
#
# Author: Jaeho Shin <netj@sparcs.org>
# Created: 2022-10-31
# See also:
# - https://gist.github.com/netj/df4f9de1fefd254ab11979be7035b5d0/#readme
# - https://cloud.google.com/iap/docs/using-tcp-forwarding
#

## make_swap_great_again.sh
#!/bin/bash

# this shell script can make a large swap quickly and put it on

set -x
set -e

if [ "$(id -u)" != 0 ]; then
            echo "This script must be run with sudo."
            exit 1

## harvard_sentences.py
# http://www.cs.cmu.edu/afs/cs.cmu.edu/project/fgdata/OldFiles/Recorder.app/utterances/Type1/harvsents.txt
# taken from here ^ and pythonified


h1 = [
	"The birch canoe slid on the smooth planks.",
	"Glue the sheet to the dark blue background.",
	"It's easy to tell the depth of a well.",
	"These days a chicken leg is a rare dish.",
	"Rice is often served in round bowls.",

## make_user_gen_ssh.sh
#!/bin/bash

NEW_USER=$1
set -e

if [ -z "$NEW_USER" ];then
        echo "Please provide user as arg... exiting."
        exit 1
fi

## autogpuswitch.sh
#!/usr/bin/bash

# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
# You would have to create an xorg.conf file for your Nvidia setup		#
# before using this script! It can be done by running:				#
#										#
#	nvidia-xconfig -o /etc/X11/xorg.conf.nvidia				#
#										#
# Make sure your system has eGPU connected and a monitor plugged into the GPU.	#
# The reason I've never automated this is that you have to have it all plugged	#

## gpuswitch.service
[Unit]
Description=GPU Switcher
After=systemd-user-sessions.service plymouth-quit.service
Before=display-manager.service

[Service]
ExecStart=/usr/local/bin/autogpuswitch.sh
Restart=no
Type=oneshot
RemainAfterExit=yes

## keras_resnet_api.py
#!/usr/bin/env python

import numpy as np
import keras
import tensorflow as tf
from keras.applications import ResNet50
from keras.preprocessing import image as image_utils
from keras.applications.resnet50 import preprocess_input, decode_predictions

import requests

## latency.txt
Latency Comparison Numbers
--------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD
	#!/usr/bin/env bash
	# ~/.ssh/gcp-start-iap-tunnel-ssh-proxy-magic.sh
	# a script to be used as SSH ProxyCommand to allow fully functional SSH access to any Google Cloud Compute Engine VMs allowing IAP access
	#
	# Author: Jaeho Shin <netj@sparcs.org>
	# Created: 2022-10-31
	# See also:
	# - https://gist.github.com/netj/df4f9de1fefd254ab11979be7035b5d0/#readme
	# - https://cloud.google.com/iap/docs/using-tcp-forwarding
	#
	#!/bin/bash

	# this shell script can make a large swap quickly and put it on

	set -x
	set -e

	if [ "$(id -u)" != 0 ]; then
	echo "This script must be run with sudo."
	exit 1
	# http://www.cs.cmu.edu/afs/cs.cmu.edu/project/fgdata/OldFiles/Recorder.app/utterances/Type1/harvsents.txt
	# taken from here ^ and pythonified


	h1 = [
	"The birch canoe slid on the smooth planks.",
	"Glue the sheet to the dark blue background.",
	"It's easy to tell the depth of a well.",
	"These days a chicken leg is a rare dish.",
	"Rice is often served in round bowls.",
	#!/bin/bash

	NEW_USER=$1
	set -e

	if [ -z "$NEW_USER" ];then
	echo "Please provide user as arg... exiting."
	exit 1
	fi
	#!/usr/bin/bash

	# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
	# You would have to create an xorg.conf file for your Nvidia setup #
	# before using this script! It can be done by running: #
	# #
	# nvidia-xconfig -o /etc/X11/xorg.conf.nvidia #
	# #
	# Make sure your system has eGPU connected and a monitor plugged into the GPU. #
	# The reason I've never automated this is that you have to have it all plugged #
	[Unit]
	Description=GPU Switcher
	After=systemd-user-sessions.service plymouth-quit.service
	Before=display-manager.service

	[Service]
	ExecStart=/usr/local/bin/autogpuswitch.sh
	Restart=no
	Type=oneshot
	RemainAfterExit=yes
	#!/usr/bin/env python

	import numpy as np
	import keras
	import tensorflow as tf
	from keras.applications import ResNet50
	from keras.preprocessing import image as image_utils
	from keras.applications.resnet50 import preprocess_input, decode_predictions

	import requests
	Latency Comparison Numbers
	--------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD