Amazon Web Services - SALSAHPC

Amazon Web Services - SALSAHPC

Introduction to Amazon Web Services Thilina Gunarathne Salsa Group, Indiana University. With contributions from Saliya Ekanayake. Introduction Fourth Paradigm Data intensive scientific discovery DNA Sequencing machines, LHC Commercial Cloud Platforms Amazon Web Services Microsoft Azure Platform Google AppEngine Cloud Computing

On demand computational services over web Spiky compute needs of the scientists Horizontal scaling with no additional cost Increased throughput Cloud infrastructure services Storage, messaging, tabular storage Cloud oriented services guarantees Virtually unlimited scalability Amazon Web Services Compute Elastic Compute Service (EC2) Elastic MapReduce Auto Scaling Storage Simple Storage Service (S3)

Elastic Block Store (EBS) AWS Import/Export Messaging Simple Queue Service (SQS) Simple Notification Service (SNS) Database SimpleDB Relational Database Service (RDS) Content Delivery CloudFront Networking Elastic Load Balancing Virtual Private Cloud

Monitoring CloudWatch Workforce Mechanical Turk Amazon Web Services Compute Elastic Compute Service (EC2) Elastic MapReduce Auto Scaling Storage Simple Storage Service (S3) Elastic Block Store (EBS) AWS Import/Export Messaging Simple Queue Service (SQS)

Simple Notification Service (SNS) Database SimpleDB Relational Database Service (RDS) Content Delivery CloudFront Networking Elastic Load Balancing Virtual Private Cloud Monitoring CloudWatch Workforce Mechanical Turk

Demo Application Job queue based embarrassingly parallel application execution BLAST, Monte Carlo simulations, many image processing applications, parametric studies Cap3 Sequence Assembly* Assembles DNA sequences by aligning and merging sequence fragments to construct whole genome sequences Executable available at http://seq.cs.iastate.edu/cap3.html Demo programs http://salsahpc.indiana.edu/tutorial/apps/aws/ * Huang, X. and Madan, A. (1999) CAP3: A DNA sequence assembly program. Genome Res., 9, 868-877. Sequence Assembly in the Clouds

Cap3 parallel efficiency Cap3 Per core per file (458 reads in each file) time to process sequences Cost to assemble to process 4096 FASTA files* Amazon AWS total :11.19 $ Compute 1 hour X 16 HCXL (0.68$ * 16) = 10.88 $ 10000 SQS messages = 0.01 $ Storage per 1GB per month = 0.15 $ Data transfer out per 1 GB = 0.15 $ Azure total : 15.77 $ Compute 1 hour X 128 small (0.12 $ * 128) = 15.36 $ 10000 Queue messages = 0.01 $

Storage per 1GB per month = 0.15 $ Data transfer in/out per 1 GB = 0.10 $ + 0.15 $ Tempest (amortized) : 9.43 $ 24 core X 32 nodes, 48 GB per node Assumptions : 70% utilization, write off over 3 years, including support * ~ 1 GB / 1875968 reads (458 reads X 4096) Architecture Security Credentials Access Keys Making a REST or Query API request JAVA SDK for S3, SQS, SimpleDB

EC2 Key Pairs Launching/connecting to EC2 instances X.509 Certificate SOAP API Command line tools AWS Toolkit for Eclipse Open source plug-in for Eclipse AWS Java SDK Java API for AWS services Amazon SimpleDB management Configure, edit, query Amazon EC2 management Deploy, debug, manage

Installing AWS Toolkit in Eclipse Installing Java 1.5 or higher Eclipse 3.5 or higher (Java EE distribution recommended) http://aws.amazon.com/eclipse http://media.amazonwebservices.com/videos/ecli pse-java-sdk-video.html Simple Storage Service (S3) Internet Data Storage Reliable, Simple, Scalable, and Inexpensive Three Concepts Buckets Analogous to a folder with no nesting URL accessible Option to enforce geographical constraints

Objects Actual data stored in buckets, e.g. PDF, Video, etc. Up to 5 gigabytes Unlimited number of objects Retrievable via HTTP, HTTPS, or BitTorrent Private, public or selectively for users Keys Unique key to identify each object in a bucket Simple Storage Service (S3) Access Logs Option to enable to logs for buckets

Pricing Data storage 0.15$ per GB for first 50TB to 0.055$ per GB for over 5000TB Data transfer in 0.1$ per GB (free till Nov,2010) Data Transfer out 0.15$ per GB up to 10TB to 0.08$ per GB for over 150TB Requests PUT, COPY, POST, LIST -> 0.01 $ per 1000 requests Others -> 0.01$ for 10,000 requests Reduced Redundant Storage 2/3 of the storage cost Using S3 as the Data Storage

S3 management console Uploading the input data to S3 Downloading/uploading files (s3 objects) programmatically Run Sample AWSStepOne eclipse project AWS Import/Export Accelerates Moving Large Scale Data In to and out of AWS using portable storage Utilized Amazons high-speed internal network Often faster than Internet upload/download for large data Simple Steps

Prepare a portable storage device Request AWS with S3 bucket, key, and shipping address Receive an ID, digital signature, an AWS shipping address Identify and authenticate storage device with digital signature Ship it and wait for Amazon to ship it back Data migration, content distribution, offsite backup, disaster recovery, direct data interchange Simple Queue Service Reliable and Scalable Distributed Messaging Framework Create, store, and retrieve text messages (up to 8 KB) Eventual consistency Messages Stored until retrieved or four days MessageID, ReceiptHandle, MD5OfBody, Body

Queues Possible to create unlimited number of queues Concerns Queue order, i.e. FIFO, is not guaranteed Message deletion in a queue is not guaranteed Querying a queue is not guaranteed to return all messages Guarantee at least once delivery, but not exactly once Simple Queue Service Visibility Timeout When received, the message will be locked in the queue for a given time Message reappears when the lock expires, unless deleted by the earlier recipient Access through REST as well as SOAP APIs Queue sharing Pricing 0.01$ for 10,000 requests

Data transfer in 0.10$ per GB after Nov, 2010 Data transfer out 0.15$ per GB up to 10TB TO 0.08$ per GB over 150 TB Using the Queue to Schedule Jobs Queue Operations CreateQueue putMessage getMessage visibility time out deleteMessage Fault tolerance Run sample AWSSampleTwo Eclipse project

Simple Notification Service (SNS) Notification Service Scalable, flexible, and cost-effective Topic based publishing Multiple protocol support, e.g. HTTP, email, etc. Eliminates polling through push mechanism Simple Steps Create a topic Identify subject or event type Set policies Publisher/subscriber limiting, protocol, etc. Add subscribers Publish message SimpleDB Non-relational data store

No need to pre-define schema Dataset Indexing and Querying Framework Highly available, scalable, secure, and fast Store and retrieve structured data Eventual consistency Optional consistent reads No transactions Conditional puts/deletes Condition based on existing value SimpleDB Domains Containers to store and query structured data Analogous to a spreadsheet No cross domain querying

Items Individual objects within domains Analogous to a row in worksheet Contains attributes with values; similar to columns and cells SimpleDB Limitations Domain size, domains per AWS account, Attributes, etc. Pricing Free tier 25 machine hours, 1 GB storage Machine utilization 0.14$ per machine hour Data transfer in 0.10$ per GB after Nov, 2010

Data transfer out 0.15$ per GB up to 10TB TO 0.08$ per GB over 150 TB Structured storage 0.25$ per GB per month Using the SimpleDB for monitoring & metadata storage Operations CreateDomain ReplaceableItem List batchPutAttributes Run sample AWSSampleThree Eclipse project Check the Eclipse SimpleDB management view

Relational Database Service (RDS) Relational Database as-a-service Full capabilities of MySQL database Easy deployment, managed, secure, scalable, and reliable Simple Steps Use AWS Management Console/API to launch a database instance (DB Instance) Connect to DB Instance with any MySQL supported tool Monitor through Amazon CloudWatch Features Automated backups DB snapshots Multi-AZ deployments Enhanced availability though multiple availability zones SimpleDB vs RDS SimpleDB

No administrative burden at all Scales up/down automatically Highly available No downtime No joins, no transactions Flexible RDS Existing applications that require relational database Need to decide the scaling decisions How much storage, what size instance, etc Elastic Compute Service Lease Linux as well as Windows VMs 32 bit as well as 64 bit VMs Pay as you go Just a credit card to get going

Dynamically scale up/down Increase throughput by horizontal scaling for the same cost root access to VMs Pre-configured, template images Create AMI to store customized images Elastic Compute Service Purchasing options On demand Reserved One time fee + usage Spot Bit for unused EC2 capacity Sometimes going 33% of the price of on demand Cluster compute instances

Elastic IP addresses Elastic Compute Service Pricing Standard, High-memory, High-CPU, cluster Instance Type Memory EC2 compute units Actual CPU cores Cost per hour

Large Extra Large 7.5 GB 15 GB 4 8 2 X (~2Ghz) 4 X (~2Ghz) 0.34$ 0.68$ High CPU Extra Large 7 GB

20 8 X (~2.5Ghz) 0.68$ 68.4 GB 26 8X (~3.25Ghz) 2.40$ 23 GB 33.5 *

1.60$ High Memory 4XL Cluster 4XL * 2 x Intel Xeon X5570, quad-core Nehalem architecture Sequence Assembly Performance with different EC2 Instance Types Amortized Compute Cost Compute Cost (per hour units) 6.00 Compute Time 2000

5.00 1000 2.00 500 1.00 6 L4X HM HM 4X L- 2

2 x1 x8 6 x1 HC XL -2 -2 HC ge

Xl ar XL -4 x2 8 erg x8 0.00 x4 0 La

Cost ($) 3.00 Compute Time (s) 4.00 1500 GTM Interpolation performance with different EC2 Instance Types 600 Amortized Compute Cost 5

Compute Cost (per hour units) 4.5 Compute Time 500 4 3.5 400 Cost ($) 300 2.5 2

200 1.5 1 100 0.5 0 0 L g ar e

-8 x2 X g lar e -4 x4 H L CX

-2 x8 HC XL 2 x1 6 EC2 HM4XL best performance. EC2 HCXL most economical. EC2 Large most efficient HM L

4X -2 x8 HM 4 XL 2 x1 6 Compute Time (s)

3 HPC in AWS Newest announcement Cluster compute instances Features Ability to group them in to clusters Low latency full duplex 10 Gbps between instances Published processor architecture Hardware virtual machine Limitations No spot or reserved instances No Auto scaling CloudWatch Monitor Amazon Cloud Resources EC2 instances, EBS volumes, Elastic Load Balancers, and RDS database

instances Insight to resource utilization, performance, and demand patterns Exposed through Amazon Management Console, API, command line tools Pay only for monitoring EC2 instances Enables AutoScaling for EC2 instances Dynamically add/remove instances based on CloudWatch metrics Pricing 0.015$ per instance hour Auto Scaling Automatically Scale Up/Down EC2 Capacity Conditions are set based on CloudWatch metrics Seamlessly handles demand spikes and drops Consumed through API/command line tools Common Uses

Automatically scaling EC2 fleet Close follow up of the demand curve Maintaining EC2 fleet at a fixed size Keep healthy EC2 instance number constant Auto scaling with Elastic Load Balancing Efficient load balancing Pricing Free with CloudWatch Deploying the Application in EC2 Launching instances Spot instances Security groups Log-in to instances Public AMI for this demo ami-af0ae1c6 You need to fill you keys

AMI Amazon Machine Images Installing the program Saving AMI Run the Program Launch the workers Run the Driver program Monitor using CloudWatch Elastic MapReduce MapReduce as-a-service Utilizes Apache Hadoop, Amazon EC2, and Amazon S3 Simple Steps Develop MapReduce program Many language support, e.g. Pig, Java, Ruby, C++, etc.

Upload data to S3 Create and monitor job flow through AWS Management Console/command line/API Pros Reliable, secure, elastic, and easy Third party tools Seamless integration with EC2, S3 Cons No tweaking of Hadoop Only supports Hadoop MapReduce framework EMR bucket names S3N Native File System for Hadoop Bucket names should not contain underscores _ Bucket names should be between 3 and 63 characters long Bucket names should not end with a dash Tips for EMR

Include at least 3 slashes in the paths S3n://wc-input/ Do not use an existing bucket for output More tips http://soam.org/?p=59 Running WordCount using EMR Upload data to S3 Create a logs folder Create job flow Debugging & logging Monitoring using Lynx

Download output Elastic Block Store (EBS) Data you save in the running instance are not persistent Block level storage volumes Off the instance persistent storage Ideal for applications like databases Pricing 0.10 $ per GB per month provisioned 0.10 $ per million I/O requests Elastic Load Balancing Automatic Distribution of Incoming Traffic Distribute across single or multiple Availability Zones Avoid routing to unhealthy EC2 instances Session affinity load balancing Metrics reported by CloudWatch

Auto scale capacity Greater fault tolerance Virtual Private Cloud (VPC) Secure and Seamless Bridge Between a companys IT infrastructure and AWS cloud Isolated AWS compute resources via VPN Extend existing management capabilities to cloud resources, e.g. security, firewalls, etc. Features Bridge with encrypted VPN connection Add EC2 instances to VPC Route traffic between VPC and Internet over VPN to examine/monitor data flow Pricing 0.05$ per VPN connection per hour Data transfer out 0.15$ per GB to 0.08$ per GB

CloudFront Content Delivery as-a-service Delivers static and streaming content Global network of edge locations US, Europe, Hong Kong/Singpore, Japan Automatic routing of objects to nearest edge location Reliable, scalable, and fast Simple Steps Store the original versions of files in a S3 bucket Create a distribution and register the bucket Use the distributions domain name to as an access point Mechanical Turk Marketplace for Human Intelligence Work Access a virtual community of on-demand workers Programmatically access marketplace

Define Human Intelligence Tasks (HITs) Identifying objects in an image, transcribing audio, etc. Load HITs to marketplace Qualify workforce Enable qualification tests for tasks requiring special skills Pay only for accepted work/output Retrieve results via service API Thank You! Questions? Acknowledgments Prof. Geoffrey Fox, Dr. Judy Qui, Saliya Ekanayake, Tak-Lon Wu (Stephen) and the Salsa group Dr. Ying Chen and Alex De Luca from IBM Almaden Research Center

Virtual School Organizers

Recently Viewed Presentations

  • MS Excel 2007 Management Information Systems 1 Overview

    MS Excel 2007 Management Information Systems 1 Overview

    It displays multiple cells that together make up a grid consisting of rows and columns, each cell containing either . alphanumeric. text or numeric values. A spreadsheet cell may alternatively contain a . formula
  • The Business Case for Building the Janssen Brand

    The Business Case for Building the Janssen Brand

    *Two-sided Exact Clopper-Pearson 95% CI; ‡Includes ARVs and booster used at screening. Data not reported for patients who had previously used 3 or 4 ARVs prior to baseline; §DRV with RTV or COBI, ATV with RTV or COBI, and LPV...
  • ¡Yo Soy Yo!

    ¡Yo Soy Yo!

    Cadadía: Habla. español. 8 minutoscadadía. Aprende. el . vocabulario. nuevo. write each word and definition 5-10 times each or make flashcards, quizlet.com is a good resource y
  • Lesson 1 - 1 Patterns & Expressions

    Lesson 1 - 1 Patterns & Expressions

    3. What are the rational roots of . ??=?3−6?2−13?+42 Applying Rational Root Theorem ±1,±2, ±3, ±6, ±7, ±14, ±21,±42 Step 2: Test each possible rational root in original function until you find a root. Do synthetic substitution until get R0
  • Forestry Equipment - Southampton County

    Forestry Equipment - Southampton County

    Forestry Equipment Competition Altimeter (Haga Altimeter shown) - measures height of trees and can also be used to measure slope. Back Pack Fire Pump (Indian Backpack Firefighting Pump shown)- when filled with water, this hand-operated pump can be used to...
  • Environmental risk factors of autism spectrum disorders: a ...

    Environmental risk factors of autism spectrum disorders: a ...

    Large birth cohort study in Bristol area of England. Approx 14,000 mothers recruited in pregnancy 1991-92. Data from Questionnaires, clinical assessments, biological samples, record linkage available on mothers and children during pregnancy and multiple times since then
  • What makes for a successful merger? Peter Scott

    What makes for a successful merger? Peter Scott

    The leaders of both firms need to be 'ad idem' on the vision. PETER SCOTT CONSULTING. PETER SCOTT CONSULTING Ensure CULTURES are compatible. Compatible - not necessarily the same - the laws of magnetism! Are we like them? Do we...
  • Fundamental Particles, Fundamental Questions Professor Elizabeth H. Simmons

    Fundamental Particles, Fundamental Questions Professor Elizabeth H. Simmons

    This ring, for example, is made up of only 2 kinds of atoms: gold (Au) and Carbon (C) Periodic table The periodic table lists about 114 atoms with distinct properties: mass, crystal structure, melting point… The range and pattern of...