Manjong Han iBluemind

Consumer-grade GPUs in an OpenStack system (NVIDIA GPUs)

Assumptions

This assumes you have GTX980 cards in your system (PCI id 10de:13c0 & 10de:0fbb per card). Just add more IDs for other cards in order to make this more generic. This also assumes nova uses qemu-kvm as the virtualization hypervisor (qemu-system-x86_64). This seems to be the default on OpenStack Newton when installed using openstack-ansible.

We assume OpenStack Newton is pre-installed and that we are working on a Nova compute node. This has been tested on an Ubuntu 16.04 system where I installed OpenStack AIO version 14.0.0 (different from the git tag used in the instructions!): http://docs.openstack.org/developer/openstack-ansible/developer-docs/quickstart-aio.html

Prepare the system for GPU passthrough (set up IOMMU/vfio/...)

Note: This is heavily based on information from https://wiki.archlinux.org/index.php/PCI_passthrough_via_OVMF#Enabling_IOMMU adapted for Ubuntu 16.04

스프링부트 소개

발표영상

0. 스프링부트SpringBoot란?

Spring Boot makes it easy to create stand-alone, production-grade Spring based Applications that you can "just run". We take an opinionated view of the Spring platform and third-party libraries so you can get started with minimum fuss. Most Spring Boot applications need very little Spring configuration.

스프링부트는 단독실행되는, 실행하기만 하면 되는 상용화 가능한 수준의, 스프링 기반 애플리케이션을 쉽게 만들어낼 수 있다.
최소한의 설정으로 스프링 플랫폼과 서드파티 라이브러리들을 사용할 수 있도록 하고 있다.

The introduction to Reactive Programming you've been missing

(by @andrestaltz)

This tutorial as a series of videos

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

Docker 치트 시트

한국어 번역(초벌): nacyot
같이 읽으면 좋은 문서들

왜 Docker를 사용해야하는가?

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

Backend Architectures

Twitter

ror, scala, jetty, erlang, thrift, mongrel, comet server, my-sql, memchached, varnish, kestrel(mq), starling, gizzard, cassandra, hadoop, vertica, munin, nagios, awstats

Introduce Gizzard of Twitter - 트위터의 새로운 분산 관리 라이브러리 Gizzard를 소개합니다.
The Architecture Twitter Uses to Deal with 150M Active Users, 300K QPS, a 22 MB/S Firehose, and Send Tweets in Under 5 Seconds
Scaling Twitter: Making Twitter 10000 Percent Faster

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

	"""
	The most atomic way to train and run inference for a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	Java.perform(function() {

	var array_list = Java.use("java.util.ArrayList");
	var ApiClient = Java.use('com.android.org.conscrypt.TrustManagerImpl');

	ApiClient.checkTrustedRecursive.implementation = function(a1, a2, a3, a4, a5, a6) {
	// console.log('Bypassing SSL Pinning');
	var k = array_list.$new();
	return k;
	}

	# Original Rails controller and action
	class EmployeesController < ApplicationController
	def create
	@employee = Employee.new(employee_params)

	if @employee.save
	redirect_to @employee, notice: "Employee #{@employee.name} created"
	else
	render :new
	end