HPC Clusters as code in the [almost]* Infinite cloud

Science is one of the greatest areas of computation Amazon huge, really disruptive, impact what we are about

Research means Collaboration Map of scientific collaboration between researchers - Olivier H. Beauchesne - http://bit.ly/e9ekp2

Existing 1. Oregon 2. California 3. Virginia 4. Dublin 5. Frankfurt 6. Singapore 7. Sydney 8. Seoul 9. Tokyo 10. Sao Paulo 11. Beijng 12. US GovCloud 1. Ohio 2. India 3. UK 4. Canada 5. China+1 AWS Region Availability Zone regions are sovereign leaves your data never

More time spent computing the data than moving the data.

Peak: 58K cores Valley: 12K cores

In the first year: Over 400,000 scenes available Over 1 billion hits globally Used for new product development by: Colin Reilly Senior Director GIS NYC Department of IT & Telecom

ESA, Planet Labs, Copernicus data from ESA s Sentinels & Zooniverse The first live public test for an effort dubbed the Planetary Response Network (PRN) Within 2 hours of the Ecuador test project going live with a first set of 1,300 images, each photo had been checked at least 20 times. It was one of the fastest responses I ve seen, says Brooke Simmons, an astronomer at the University of California, San Diego, who leads the image processing. Steven Reece, who heads the Oxford team s machine-learning effort, says that results a heat map of damage with possible road blockages were ready in another two hours.

Cray Supercomputer

A top500 supercomputer 2013-style

Introducing Alces Flight - self-scaling HPC clusters instantly ready to compute, billed by the hour and using the AWS Spot market by default to achieve supercomputing for ~1c per core per hour. 750+ popular scientific applications AWS Marketplace immediately http://boofla.io/u/alcesflight

Virtual Private Cloud Auto-scaling group Head node Instance /shared Compute node Instance Compute node Instance Compute node Instance Compute node Instance 10G Network Head Instance 2 or more cores (as needed) CentOS 7.x OpenMPI, gcc etc Choice of scheduler: SGE (now) PBSpro & SLURM (coming soon) Compute Instances 2 or more cores (as needed) CentOS 7.x, Amazon Linux Auto Scaling group driven by scheduler queue length. Can start with 0 (zero) nodes and only scale when there are jobs.

Wall clock time: ~1 hour Wall clock time: ~1 week Cost: the same

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C4 Intel Xeon E5-2666 v3, custom built for AWS. Intel Haswell, 16 FLOPS/tick 2.9 GHz, turbo to 3.5 GHz Feature Processor Number Intel Smart Cache Instruction Set Specification E5-2666 v3 25 MiB 64-bit Instruction Set Extensions AVX 2.0 Lithography Processor Base Frequency Max All Core Turbo Frequency Max Turbo Frequency Intel Turbo Boost Technology 2.0 Intel vpro Technology Intel Hyper-Threading Technology Intel Virtualization Technology (VT-x) Intel Virtualization Technology for Directed I/O (VT-d) Intel VT-x with Extended Page Tables (EPT) 22 nm 2.9 GHz 3.2 GHz 3.5 GHz (available on c4.2xlarge) Yes Yes Yes Yes Yes http://docs.aws.amazon.com/awsec2/latest/userguide/c4-instances.html Intel 64 Yes

All the traditional command-line tools will be familiar, but you can also create an Alces session and immediately launch a desktop view of your cluster to run graphical apps. Command Line (ssh) Graphical Console

graphical console simultaneously with your collaborators work together with the visual console in realtime Make more discoveries faster

There are cluster filesystem options, too for when you need extreme I/O scaling.

Disrupting research, wherever it s happening.

39 years of computational chemistry in 9 hours Novartis ran a project that involved virtually screening 10 million compounds against a common cancer target in less than a week. They calculated that it would take 50,000 cores and close to a $40 million investment if they wanted to run the experiment internally. Partnering with Cycle Computing and Amazon Web Services (AWS), Novartis built a platform thst ran across 10,600 Spot Instances (~87,000 cores) and allowed Novartis to conduct 39 years of computational chemistry in 9 hours for a cost of $4,232. Out of the 10 million compounds screened, three were successfully identified.

CHILES will produce the first HI deep field, to be carried out with the VLA in B array and covering a redshift range from z=0 to z=0.45. The field is centered at the COSMOS field. It will produce neutral hydrogen images of at least 300 galaxies spread over the entire redshift range. The team at ICRAR in Australia have been able to implement the entire processing pipeline in the cloud for around $2,000 per month by exploiting the SPOT market, which means the $1.75M they otherwise needed to spend on an HPC cluster can be spent on way cooler things that impact their research like astronomers.

1. AWS Account 3. A problem to solve