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Amazon drops prices of Linux AMIs by ~20%
Amazon cloud gets more exciting. We are still waiting for the Oracle and Google public clouds (compute) to open up out of beta! See their (rather cluttered) blog
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Today, we are excited to announce a new generation of the original Amazon EC2 instance family. Second generation Standard instances (M3 instances) provide customers with the same balanced set of CPU and memory resources as first generation Standard instances (M1 instances) while providing customers with 50% more computational capability/core.
M3 instances are currently available in two instance types; extra-large (m3.xlarge) and double extra-large (m3.2xlarge). Examples of applications that can benefit from the additional CPU horsepower of these new instances include media encoding, batch processing, web servers, caching fleets, and many others. Currently, M3 instances are available in the US East (N. Virginia) Region starting at a Linux On-Demand price of $0.58/hr for extra-large instances. Customers can also purchase M3 instances as Reserved Instances or as Spot instances. We will introduce M3 instances in additional regions in the coming months.
To learn more about Amazon EC2 instance types and to find out which instance type might be useful for you, please visit the Amazon EC2 Instance type page.
Pricing Change for M1 Standard Instances
Along with the introduction of the M3 Standard instance family, we are announcing a reduction in Linux On-Demand pricing for M1 Standard instances in the US East (N. Virginia) and US West (Oregon) Regions by almost 19%. The new pricing is effective from November 1 and is described in the following table
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You can find out more about pricing for all Amazon EC2 instances by visiting the Amazon EC2 pricing page.
Windows Azure and Amazon Free offer
Image via Wikipedia
For Hi-Computing folks try out Azure for free-
Windows Azure Platform
Introductory Special
This promotional offer enables you to try a limited amount of the Windows Azure platform at no charge. The subscription includes a base level of monthly compute hours, storage, data transfers, a SQL Azure database, Access Control transactions and Service Bus connections at no charge. Please note that any usage over this introductory base level will be charged at standard rates.
Included each month at no charge:
Any monthly usage in excess of the above amounts will be charged at the standard rates. This introductory special will end on March 31, 2011 and all usage will then be charged at the standard rates. Standard Rates: Windows Azure
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http://aws.amazon.com/ec2/pricing/
Free Tier*
As part of AWS’s Free Usage Tier, new AWS customers can get started with Amazon EC2 for free. Upon sign-up, new AWScustomers receive the following EC2 services each month for one year:
- 750 hours of EC2 running Linux/Unix Micro instance usage
- 750 hours of Elastic Load Balancing plus 15 GB data processing
- 10 GB of Amazon Elastic Block Storage (EBS) plus 1 million IOs, 1 GB snapshot storage, 10,000 snapshot Get Requests and 1,000 snapshot Put Requests
- 15 GB of bandwidth in and 15 GB of bandwidth out aggregated across all AWS services
Paid Instances-
| Standard On-Demand Instances | Linux/UNIX Usage | Windows Usage |
|---|---|---|
| Small (Default) | $0.085 per hour | $0.12 per hour |
| Large | $0.34 per hour | $0.48 per hour |
| Extra Large | $0.68 per hour | $0.96 per hour |
| Micro On-Demand Instances | ||
| Micro | $0.02 per hour | $0.03 per hour |
| High-Memory On-Demand Instances | ||
| Extra Large | $0.50 per hour | $0.62 per hour |
| Double Extra Large | $1.00 per hour | $1.24 per hour |
| Quadruple Extra Large | $2.00 per hour | $2.48 per hour |
| High-CPU On-Demand Instances | ||
| Medium | $0.17 per hour | $0.29 per hour |
| Extra Large | $0.68 per hour | $1.16 per hour |
| Cluster Compute Instances | ||
| Quadruple Extra Large | $1.60 per hour | N/A* |
| Cluster GPU Instances | ||
| Quadruple Extra Large | $2.10 per hour | N/A* |
* Windows is not currently available for Cluster Compute or Cluster GPU Instances. |
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NOTE- Amazon Instance definitions differ slightly from Azure definitions
http://aws.amazon.com/ec2/instance-types/
Available Instance Types
Standard Instances
Instances of this family are well suited for most applications.
Small Instance – default*
1.7 GB memory
1 EC2 Compute Unit (1 virtual core with 1 EC2 Compute Unit)
160 GB instance storage
32-bit platform
I/O Performance: Moderate
API name: m1.small
Large Instance
7.5 GB memory
4 EC2 Compute Units (2 virtual cores with 2 EC2 Compute Units each)
850 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.large
Extra Large Instance
15 GB memory
8 EC2 Compute Units (4 virtual cores with 2 EC2 Compute Units each)
1,690 GB instance storage
64-bit platform
I/O Performance: High
API name: m1.xlarge
Micro Instances
Instances of this family provide a small amount of consistent CPU resources and allow you to burst CPU capacity when additional cycles are available. They are well suited for lower throughput applications and web sites that consume significant compute cycles periodically.
Micro Instance
613 MB memory
Up to 2 EC2 Compute Units (for short periodic bursts)
EBS storage only
32-bit or 64-bit platform
I/O Performance: Low
API name: t1.micro
High-Memory Instances
Instances of this family offer large memory sizes for high throughput applications, including database and memory caching applications.
High-Memory Extra Large Instance
17.1 GB of memory
6.5 EC2 Compute Units (2 virtual cores with 3.25 EC2 Compute Units each)
420 GB of instance storage
64-bit platform
I/O Performance: Moderate
API name: m2.xlarge
High-Memory Double Extra Large Instance
34.2 GB of memory
13 EC2 Compute Units (4 virtual cores with 3.25 EC2 Compute Units each)
850 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.2xlarge
High-Memory Quadruple Extra Large Instance
68.4 GB of memory
26 EC2 Compute Units (8 virtual cores with 3.25 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: m2.4xlarge
High-CPU Instances
Instances of this family have proportionally more CPU resources than memory (RAM) and are well suited for compute-intensive applications.
High-CPU Medium Instance
1.7 GB of memory
5 EC2 Compute Units (2 virtual cores with 2.5 EC2 Compute Units each)
350 GB of instance storage
32-bit platform
I/O Performance: Moderate
API name: c1.medium
High-CPU Extra Large Instance
7 GB of memory
20 EC2 Compute Units (8 virtual cores with 2.5 EC2 Compute Units each)
1690 GB of instance storage
64-bit platform
I/O Performance: High
API name: c1.xlarge
Cluster Compute Instances
Instances of this family provide proportionally high CPU resources with increased network performance and are well suited for High Performance Compute (HPC) applications and other demanding network-bound applications. Learn more about use of this instance type for HPC applications.
Cluster Compute Quadruple Extra Large Instance
23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge
Cluster GPU Instances
Instances of this family provide general-purpose graphics processing units (GPUs) with proportionally high CPU and increased network performance for applications benefitting from highly parallelized processing, including HPC, rendering and media processing applications. While Cluster Compute Instances provide the ability to create clusters of instances connected by a low latency, high throughput network, Cluster GPU Instances provide an additional option for applications that can benefit from the efficiency gains of the parallel computing power of GPUs over what can be achieved with traditional processors. Learn moreabout use of this instance type for HPC applications.
Cluster GPU Quadruple Extra Large Instance
22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge
versus-
Windows Azure compute instances come in five unique sizes to enable complex applications and workloads.
| Compute Instance Size | CPU | Memory | Instance Storage | I/O Performance |
|---|---|---|---|---|
| Extra Small | 1 GHz | 768 MB | 20 GB* | Low |
| Small | 1.6 GHz | 1.75 GB | 225 GB | Moderate |
| Medium | 2 x 1.6 GHz | 3.5 GB | 490 GB | High |
| Large | 4 x 1.6 GHz | 7 GB | 1,000 GB | High |
| Extra large | 8 x 1.6 GHz | 14 GB | 2,040 GB | High |
*There is a limitation on the Virtual Hard Drive (VHD) size if you are deploying a Virtual Machine role on an extra small instance. The VHD can only be up to 15 GB.
Related Articles
- Blog Post: New Year’s Resolution – Test Drive Windows Azure platform for 30 Days No Credit Card Required (blogs.msdn.com)
- Cloud Throw Down: Part 3 – Relational Databases and Instance Prices (cloudave.com)
- Amazon To Offer Free Cloud Services (informationweek.com)
- Microsoft Is Serious To Take On Amazon Web Services (cloudave.com)
- The Four Dimensions of Cloud Provisioning (itexpertvoice.com)
- “Windows Azure Discovery Events for ISVs in Western US” and related posts (ditii.com)
- Windows Azure Free Training Kit – December (devcurry.com)
- Windows Azure Free Training Kit – December (mt-soft.com.ar)
- Windows Azure updates help with cloud migration (v3.co.uk)
Amazon goes HPC and GPU: Dirk E to revise his R HPC book
Image via Wikipedia
Amazon just did a cluster Christmas present for us tech geek lizards- before Google could out doogle them with end of the Betas (cough- its on NDA)
Clusters used by Academic Departments now have a great chance to reduce cost without downsizing- but only if the CIO gets the email.
While Professor Goodnight of SAS / North Carolina University is still playing time sharing versus mind sharing games with analytical birdies – his 70 mill server farm set in Feb last is about to get ready
( I heard they got public subsidies for environment- but thats historic for SAS- taking public things private -right Prof as SAS itself began as a publicly funded project. and that was in the 1960s and they didnt even have no lobbyists as well. )
In realted R news, Dirk E has been thinking of a R HPC book without paying attention to Amazon but would now have to include Amazon
(he has been thinking of writing that book for 5 years, but hey he’s got a day job, consulting gigs with revo, photo ops at Google, a blog, packages to maintain without binaries, Dirk E we await thy book with bated holes.
Whos Dirk E – well
http://dirk.eddelbuettel.com/
is like the Terminator of R project (in terms of unpronounceable surnames)
Back to the cause du jeure-
From
http://aws.amazon.com/ec2/hpc-applications/
but minus corporate buzz words.
Unique to Cluster Compute and Cluster GPU instances is the ability to group them into clusters of instances for use with HPC
applications. This is particularly valuable for those applications that rely on protocols like Message Passing Interface (MPI) for tightly coupled inter-node communication.
Cluster Compute and Cluster GPU instances function just like other Amazon EC2 instances but also offer the following features for optimal performance with HPC applications:
- When run as a cluster of instances, they provide low latency, full bisection 10 Gbps bandwidth between instances. Cluster sizes up through and above 128 instances are supported.
- Cluster Compute and Cluster GPU instances include the specific processor architecture in their definition to allow developers to tune their applications by compiling applications for that specific processor architecture in order to achieve optimal performance.
The Cluster Compute instance family currently contains a single instance type, the Cluster Compute Quadruple Extra Large with the following specifications:
23 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cc1.4xlarge
The Cluster GPU instance family currently contains a single instance type, the Cluster GPU Quadruple Extra Large with the following specifications:
22 GB of memory
33.5 EC2 Compute Units (2 x Intel Xeon X5570, quad-core “Nehalem” architecture)
2 x NVIDIA Tesla “Fermi” M2050 GPUs
1690 GB of instance storage
64-bit platform
I/O Performance: Very High (10 Gigabit Ethernet)
API name: cg1.4xlarge
.
Related Articles
- Amazon Announces Cluster GPU Instance for Cloud Computing (insidehpc.com)
- New EC2 Instance Type – The Cluster GPU Instance (aws.typepad.com)
- Expanding the Cloud – Adding the Incredible Power of the Amazon EC2 Cluster GPU Instances (allthingsdistributed.com)
HP goes GPU, Will software people follow
Image via Wikipedia
One more addition to the GPU stack that adds up power when combined with CPU and GPUs. For numeric computing, it may be essential to have GPU- CPU mixed software as almost all hardware people now have offered GPU-CPU products. Maybe software companies can get inspired for new kind of GPU-CPU blade server software again.
Source-
http://www.hpcwire.com/features/HP-Adds-New-HPC-Server-with-GPGPU-Option-104381494.html
But for “true” supercomputing applications, the SL390s G7 is the go-to server. Like its sibling, the SL390s comes with Xeon 5600 processors, but the option to pair the CPUs with up to three on-board NVIDIA “Fermi” 20-series GPUs puts a lot more floating point performance into this design. Customers can choose from either the M2050 or M2070 Tesla GPU modules, the only difference being the amount of graphics memory — 3 GB of GDDR5 for the M2050 versus 6 GB for the M2070. Each GPU module is served by its own PCIe Gen2 x16 channel in order to maximize bandwidth to the graphics chips. At the maximum configuration with all three Fermi GPUs and two Westmere CPUs, a single server delivers on the order of 1 teraflop of double precision performance. “So this is very much a server that has been designed for HPC,” said Turkel.
With GPUs on board, the SL390s fill out a 2U half-width tray, so up to four of these can be packed into a 4U SL6500 chassis. A CPU-only version is also available and takes up just half the space (half-width 1U), enabling twice as many Xeons to occupy the same chassis. This configuration will likely be the server of choice for the majority of HPC setups, given that GPGPU deployment is really just getting started. Pricing on the CPU-only model starts at $2,259.
And
, the ProLiant SL390s G7, provides more raw FLOPS per square inch than any server HP has delivered to date, and is the basis for the 2.4 petaflop TSUBAME 2.0 supercomputer currently being deployed at the Tokyo Institute of Technology.
Related Articles
- NextIO squeezes Nvidia GPUs into super-dense package (go.theregister.com)
- AMD Fusion reaches out to partners (v3.co.uk)
- IBM tweaks rack and blade servers (go.theregister.com)
- HP sprinkles GPU chips on new cookie sheet servers (go.theregister.com)
- DARPA Has a $25 Million GPU supercomputer Project and Dell has a 16 GPU chasis (nextbigfuture.com)
Running R on Amazon EC2 :Windows
Running R on an Amazon EC2 has following benefits-
1) Elastic Memory and Number of Processors for heavy computation
2) Affordable micro instances for smaller datasets (2 cents per hour for Unix to 3 cents per hour).
3) An easy to use interface console for managing datasets as well as processes
Running R on an Amazon EC2 on Windows Instance has following additional benefits-
1) Remote Desktop makes operation of R very easy
2) 64 Bit R can be used
3) You can also use your evaluation of Revolution R Enterprise (which is free to academics) and quite inexpensive for enterprise software for corporates.
You can thus combine R GUIs (like Rattle , R Cmdr or Deducer based upon your need for statistical analysis, data mining or graphical analysis) , with 64 Bit OS, and Revolution’s REvoScaler Package to manage huge huge datasets at a very easy to use analytics solution.
Pricing-for Computation on EC2
| Standard On-Demand Instances | Linux/UNIX Usage | Windows Usage |
|---|---|---|
| Small (Default) | $0.085 per hour | $0.12 per hour |
| Large | $0.34 per hour | $0.48 per hour |
| Extra Large | $0.68 per hour | $0.96 per hour |
| Micro On-Demand Instances | Linux/UNIX Usage | Windows Usage |
| Micro | $0.02 per hour | $0.03 per hour |
| High-Memory On-Demand Instances | ||
| Extra Large | $0.50 per hour | $0.62 per hour |
| Double Extra Large | $1.00 per hour | $1.24 per hour |
| Quadruple Extra Large | $2.00 per hour | $2.48 per hour |
| High-CPU On-Demand Instances | ||
| Medium | $0.17 per hour | $0.29 per hour |
| Extra Large | $0.68 per hour | $1.16 per hour |
| Cluster Compute Instances | ||
| Quadruple Extra Large | $1.60 per hour | N/A* |
* Windows is not currently available for Cluster Compute Instances. |
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Internet Data Transfer
The pricing below is based on data transferred “in” and “out” of Amazon EC2.
| Data Transfer In | US & EU Regions | APAC Region |
|---|---|---|
| All Data Transfer | Free until Nov 1, 2010 * |
Free until Nov 1, 2010 * |
Data Transfer Out ** |
US & EU Regions | APAC Region |
|---|---|---|
| First 1 GB per Month | $0.00 per GB | $0.00 per GB |
| Up to 10 TB per Month | $0.15 per GB | $0.19 per GB |
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Amazon EBS Volumes- To store data
Amazon EBS Snapshots to Amazon S3 (priced the same as Amazon S3)
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http://aws.amazon.com/ec2/#pricing
Other costs are optional to your needs
Based on the above- I set out to try and create a how-to DIY for running R (and RevolutionR on 64bit Windows on EC2)
1) Logon to
https://console.aws.amazon.com/ec2/home
2) Launch Windows Instance
Left Margin-AMI-
Top Windows – Select Windows 64 AMI
(note if you select SQL Server it will cost you extra)
Then go through the following steps and launch instance
For tags, etc just click on and pass (or read and create some tags to help you remember, and organize multiple instances)
In configure firewall, remember to Enable Access to RDP (Remote Desktop) and HTTP. You can choose to enable whole internet or your own ip address/es for logging in
Review and launch instance
Go to instance (leftmost margin)
Click on Instance Actions-Connect on Top Bar to see following
Download the .RDP shortcut file and
Click on Instance Actions-Request Admin Password
Have coffee (or tea is you are health minded)
Click Again on Instance Actions-Request Admin Password
Open the key pair file (or .pem file created earlier) using
notepad, and copy and paste the Private Key (looks like gibberish)- and click Decrypt.
Note the new password generated- this is your Remote Desktop Password.
Click on the .rdp file (or Shortcut file created earlier)- It will connect to your Windows instance. 
Enter the new generated password in Remote Desktop
- Login
This looks like a new clean machine with just Windows OS installed on it.
Install Chrome (or any other browser) if you do not use Internet Explorer
Install Acrobat Reader (for documentation), Revolution R Enterprise~ 490 mb (it will automatically ask to install the .NET framework-4 files) and /or R
Install packages (I recommend installing R Commander, Rattle and Deducer). Apart from the fact that these GUIs are quite complimentary- they also will install almost all main packages that you need for analysis (as their dependencies) Revolution R installs parallel programming packages by default.
If you want to save your files for working later, you can make a snapshot (go to amazon console-ec2- left margin- ABS -Snapshot- you will see an attached memory (green light)- click on create snapshot to save your files for working later
If you want to use my Windows snapshot you can work on it , just when you start your Amazon Ec2 you can click on snapshots and enter details (see snapshot name below) for making a copy or working on it for exploring either 64 bit R, or multi core cloud computing or just trying out Revolution R’s new packages for academic purposes.
