lab 1: introduction to amazon ec2 and mpi

1: Introduction to Amazon EC2 and MPI

Zubair Nabi

[email protected]

April 17, 2013

Zubair Nabi 1: Introduction to Amazon EC2 and MPI April 17, 2013 1 / 13

Outline

1 Amazon EC2

2 Message Passing Interface

Outline

1 Amazon EC2

Introduction

Elastic Compute Cloud (EC2) allows you to rent out virtual machinesand run them atop Amazon’s physical datacenters

Possible to choose from a number of machine configurationsI Vary in terms of processing power, memory configuration, and disk

Amazon Machine Image (AMI), which is a silo of preconfiguredoperating system stack and application software, is run atop these VMs

I Public AMIs work out-of-the-box with different application stacks, suchas those designed for LAMP, Drupal, etc.

Introduction

Elastic Compute Cloud (EC2) allows you to rent out virtual machinesand run them atop Amazon’s physical datacentersPossible to choose from a number of machine configurations

I Vary in terms of processing power, memory configuration, and diskspace

Introduction

Instances

Instances vary from Small to High-Memory Quadruple Extra Large andfrom Cluster GPU to High I/O Quadruple Extra Large

I M1 Small Instance:F 1.7 GB memoryF 1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)F 160 GB instance storageF 32-bit or 64-bit platform

I High-Memory Quadruple Extra Large Instance:F 68.4 GB memoryF 26 EC2 Compute Units (8 virtual core with 3.25 EC2 Compute Units each)F 1690 GB instance storageF 64-bit platform

Instances

Instances (2)

Cluster GPU Quadruple Extra Large Instance:I 22 GB memoryI 33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core)I 2 x NVIDIA Tesla “Fermi” M2050 GPUsI 1690 GB instance storageI 64-bit platform

High I/O Quadruple Extra Large Instance:I 60.5 GB memoryI 35 EC2 Compute Units (16 virtual cores)I 2 SSD-based volumes each with 1024 GB of instance storageI 64-bit platform

Instances (2)

Cluster GPU Quadruple Extra Large Instance:I 22 GB memoryI 33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core)I 2 x NVIDIA Tesla “Fermi” M2050 GPUsI 1690 GB instance storageI 64-bit platform

High I/O Quadruple Extra Large Instance:I 60.5 GB memoryI 35 EC2 Compute Units (16 virtual cores)I 2 SSD-based volumes each with 1024 GB of instance storageI 64-bit platform

Storage

Normal instances do not provide persistent storage

Changes made to a VM are lost upon termination

To remedy this, Elastic Block Store (EBS) can be used

Persistent virtual drives that give the illusion of network-attachedstorage

Storage

Storage with a simple web services interface

Web interface used to store and retrieve data, at any time, fromanywhere on the web

The unit of storage allocation is a bucket which is a container forobjects

Objects consist of object data and some metadata (key/value pairs)

Each object has a unique identifier, a key, within a bucket

Updates are atomic at the key level

Automatic replication across multiple servers

Outline

1 Amazon EC2

Language-independent communications protocol to build parallelapplications within and across machines

Interface to define virtual topology, synchronization, andcommunication between processes

I Point-to-point rendezvous-type send/receive operationsF Synchronous, asynchronous, and buffered variants

I Cartesian or graph-centric logical process topologiesI Exchanging data between process pairsI Aggregating partial results of computationsI Synchronizing nodes

Language-independent communications protocol to build parallelapplications within and across machinesInterface to define virtual topology, synchronization, andcommunication between processes

I Point-to-point rendezvous-type send/receive operations

F Synchronous, asynchronous, and buffered variantsI Cartesian or graph-centric logical process topologiesI Exchanging data between process pairsI Aggregating partial results of computationsI Synchronizing nodes

I Cartesian or graph-centric logical process topologies

I Exchanging data between process pairsI Aggregating partial results of computationsI Synchronizing nodes

I Cartesian or graph-centric logical process topologiesI Exchanging data between process pairs

I Aggregating partial results of computationsI Synchronizing nodes

I Cartesian or graph-centric logical process topologiesI Exchanging data between process pairsI Aggregating partial results of computations

I Synchronizing nodes

Features

Used for distributed memory parallelism (shared-nothing systems)

Highly efficient: Can be used for many different models of computation,therefore can be used with many different applicationsUsed for SPMD-style coding

I Single Program, Multiple Data

Low-level therefore highly efficient

Features

Highly efficient: Can be used for many different models of computation,therefore can be used with many different applications

Used for SPMD-style codingI Single Program, Multiple Data

Features

Example: Hello World!

1 #include<stdio.h>2 #include<mpi.h>34 int main (int argc, char ∗argv[])5 {

6 int rank, size;

78 MPI_Init(&argc, &argv);

9 MPI_Comm_rank(MPI_COMM_WORLD , &rank);

10 MPI_Comm_size(MPI_COMM_WORLD , &size);

11 printf("Hello world on process %d of total %d\n", rank, size);

12 MPI_Finalize();

13 return 0;

References

Running a website on Amazon EC2:http://www.diginmotion.com/faq/108-running-a-website-on-amazon-ec2.pdf

lab 1: introduction to amazon ec2 and mpi

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