Compute Cycles

Announcing ZeroCompute™: Eco-conscious, Instantaneous Utility Supercomputing

Today’s researchers are shackled by a lack of access to compute power. Novel advances in modern science and engineering demand higher performing systems to solve increasingly difficult problems.  

Cycle is pleased to announce our new intelligent orchestration software to meet these challenges, called "ZeroCompute™".

ZeroCompute solves access to remote high performance cloud computing environments with a patent pending technology designed to accelerate access to HPC and BigData systems. This approach can simultaneously manage science that might normally require brontobyte datasets, and five hundred billion concurrent jobs.

After years building Utility HPC & Utility Supercomputing software, Cycle's engineers have discovered that the fastest way to execute any algorithm is to just not run it at all.

Although seemingly obvious, by simply not running the science on any cores, we remove the computational challenges and data transfer bottlenecks of today’s BigCompute and BigData workloads. Because ZeroCompute "completes" the floating point in the nanosecond it takes the software to decide not to run anything, accordingly, the system exceeds a peak floating-point performance of over one billion petaflops, at a cost of $0.00 per flop.

By combining ZeroCompute with a nice hammock and an adult beverage, all researchers can now compute with ease. "This is earth shattering technology! For years we have been extremely worried about how can we possibly compute against such large datasets,” says Dr. James Cuff, Cycle’s Chief Technology Officer. “Now with ZeroCompute, we just don't have to worry. It’s a relief that we can kick back, and allow ZeroCompute to not run the workload for us. It’s so easy anyone can do this, simply by doing nothing!"

We have already seen wide adoption of ZeroCompute methodologies in the market, which will yield a huge slowdown in drug discovery pipelines, massive losses for some financial institutions due to lack of modeling, and engineering and manufacturing companies simply ceasing to create any new, competitive products. Thankfully, ZeroCompute will make this all very easy.

As a further benefit, ZeroCompute is exceptionally ecologically conscious. Using advanced mathematics, and not running any science, has resulted in the highest possible flops/W of any modern computing architecture.

Leaving unused compute capacity to go to waste may power a new economic collapse, increased use of streaming video, and a commodities market rise in stone wheels, caveman suits and wooden clubs; we advise going long on all cave options.  

Jason Stowe, CEO of Cycle Computing said in a statement, "We should have done this years ago! It has been a huge challenge to actually enable utility supercomputing at scale. We used to spend tremendous effort creating 50,000-core supercomputers at the push of a button; now you don't even have to push the button."

Unlike competing technology that also doesn’t make actual cloud HPC easy, ZeroCompute is fully available today, and for immediate download from file:///dev/null

Servers Are Not Houseplants: Servers Are Wheat!

Once upon a time, in the early evolution of computing, it was a time of great opulence, and all was well with the kingdom. This was a time when when every computer server had a title and they were loved and anthropomorphized by the humans. The elder humans would give them mawkish little names and take tender loving care of each and every one of them, talking to them, hugging them, feeding them individually and treating them with great care, understanding the uniqueness of each and every one.

Ah, history! It teaches us so many things! These primitives were not alone, even today the British Royalty have been known to talk to their house plants! Hands up how many of us have named our servers?  We come up with all sorts of names much inspiration has come from Starwars, names of planets, names of beverages and other popular motifs. Our friend Peter Cheslock started a lovely twitter thread, which also included replies from Pinterest. Think about it, Pinterest's entire business is about being social! Even their catchphrase is "A few (million) of your favorite things!", but still these folks don't name their servers, a UUID is just dandy!

So why is this?  Why don't we give cutesy names to our servers any more? Our answer here at cycle is:

Scale has changed everything!

The ubiquity of cloud computing and utility supercomputing clearly changes all of this. The amount of science we need to execute on a daily basis changes this. We don't have time to nourish and look after individual computer servers, or houseplants for that matter! Accordingly:

Servers Are Wheat!

Now we metaphorically plough the fields, we sow the seeds, we reap the wheat, and then we consume it. When we are done, we start all over again. The emotional attachment to wheat is not the same as houseplants. Wheat; yeah it has a job to do, just like our servers! We don't our "hug servers", servers are wheat, why would you want to hug wheat?

So then, we are now all modern day computational farmers! We have had to move from the "hunting and gathering" stage of computing into a brave new era of advanced technologies, we have had to adapt.  Because we adapted (like our ancestors) we can now grow more, with higher capacity and increased yield with considerably less effort.  Our traditional scythes have been replaced with combine harvesters! 

We are clearly out of the stone age :-)  

So, if you are an experienced farmer, why not come join us as we literally tend to fields packed with hundreds of thousands of awesome cereals! 

 

 

Enterprise HPC in the Cloud: Fortune 500 Use Cases

Cycle Computing invited some of their customers to AWS re:Invent to talk about the amazing science, analytics and discovery they are executing at scale in concert with Cycle technology platforms. Our segment was called "Enterprise HPC in the Cloud: Fortune 500 Use Cases". First up Jason Stowe Cycle Computing CEO gives a wonderful overview of why Utility Supercomputing really matters for each and every one of us!

 

However, we also thought it would be wonderful to share our customers activities with you so you may see what leading players in the field of Utility Supercomputing are doing on a day to day basis. There are four amazing talks below, each do an excellent job of highlighting the challenges and solutions for each domain.  The talks describe the use of utility supercomputers to solve real world problems in Life Science, Finance, Manufacturing, Energy, and Insurance.

The latest and greatest in advanced workloads are discussed that are helping push these industries and technologies forward through the insights gained from big data and high performance computing, including a sneak peak into what they see as coming next.

First up, Kurt Prenger and Taylor Hamilton of J & J High Performance Computing:

 

Challenges: Disparate internal clusters, lack of resource for large problem execution, and home grown systems pain.

Solutions: Cycle Computing SubmitOnce - jobs are routed to internal and external clusters via configurable intelligence based on cluster loads, data size and estimated runtimes. Single entry point for users without having to understand complex backend systems.

Next up: David Chang, Assistant Vice President of Pacific Life:

 

Challenges: Increasing complexity in product design with extensive use of Monte Carlo simulations with added issues of regulatory requirements, and hedging and risk management needs.

Solutions: More efficient modeling techniques and broader adoption of new technologies such as GPGPU.

Next, Amitabh Shukla, Director Software Engineering at Life Technologies: 

 

Challenges: Living in the age of "the thousand dollar genome and the million dollar analysis" - George Church

Solutions: Ion Reporter (tm) technology powered by Cycle Computing. IR Data Analyses with elastic CC2 instances via CycleCloud using Hadoop to bring vast data sets to the compute nodes. Cloud deployments simplify user experience, easy access, pay as you go and simple to deploy and manage solutions.

Finally, Robert Nordlund, Risk Management Technology at The Hartford Insurance Group: 

 

Challenges: Asset and Liability Modeling with a Dynamic Hedging Program. Large scale analysis with millions of policies, scenarios and trillions of calculations. All based on sensitive market movements, long time horizons and complex behaviors. 2.5 million core hour runs to target solution over a weekend.

Solutions: Two data centers 7,000 cpu and 448k CUDA cores, orchestrated by Cycle Computing's CycleServer. Cloud resources deployed to reduce cost, increase scale to explore new technology, improved algorithms and boost application performance.

We really hope you enjoyed these wonderful insights into how our customers are gaining a significant edge with Cycle Computing technologies!  If you are facing similar challenges, feel free to get in touch!

The British are coming!

Dear all, 
I wanted to announce a fantastic new member to Cycle's team, Dr. James Cuff, who is joining us as Chief Technology Officer to help us continue our breakthrough work with clients. James was formerly Director of Research Computing and Chief Technology Architect at Harvard University where he was responsible for constructing and managing  over 10PB of storage, 25,000 processors for 5,000 users to run science. Before his tenure at Harvard, James held group leadership positions at the Broad Institute and The Wellcome Trust Sanger Institute, with a PhD from Oxford. His start will also mark the start of an increasing presense in Massachusetts to address increased growth we're seeing there.

In our work day-to-day, I'm excited to have James help us better understand and help customers use our techology to do breakthrough science. As we posted a week ago, we're growing considerably, and I welcome James' vision, communication, and customer-focus as we expand to meet the scientific, finance, and engineering community's increasing needs for computing.

Thanks, 
Jason Stowe 
CEO 

Built to scale: 10,600-instance CycleCloud cluster, 39 core-years of science: $4,362!

Here is the story of a 10,600 instance (i.e. a multi-core server) HPC cluster created in 2 hours with CycleCloud on Amazon EC2 with one Chef 11 server and one purpose in mind: to accelerate life science research relating to a cancer target for a Big 10 Pharmaceutical company.

Our story begins…
First, when we got a call from our friends at Opscode about scale-testing Chef, we had just the workload in mind. As it happened, one of our life science clients was running a very large scale run against a cancer target. And let us tell you, knowing that hardcore science is being done with the infrastructure below is a very satisfying thing: 

AWS Console Output

 

That’s right, 10,598 server instances running real science! But we’re getting ahead of ourselves…

Unfortunately, we’re a bit limited in what parts of the science we can talk about, other than to say we’ve done a large-scale computational chemistry run to simulate millions of compounds that may interact with a protein associated with a form of cancer. We estimated this would take about 341,700 hours. This is very cool science, science that would take months to years on available internal capacity! More on that later…

Thankfully, our software has been doing a lot of utility supercomputing for clients, and as we mentioned last week, because of this we’re hiring.

So to tackle this problem, we decided to build software to create a CycleCloud utility supercomputer from 10,600 cloud instances, each of which was a multi-core machine! This makes this cluster the largest server-count cloud HPC environment that we know about, or has been made public to date (the former utility supercomputing leader was our 6,732 instance cluster for Schödinger from 2012).

If this cluster were a physical environment, analysts said it would occupy a 12,000 sq ft data center space, costing $44 million. Instead, we created this in 2 hours, with these 10,600 hosts, used it for 9 more, at a peak cost of $549.72 per hour, and turned it off for a total cost of $4,362. Wow!

In creating this environment, we’re also happy to tell you we used a single open-source Chef 11 server on a CC2 class machine! It took a mere two hours to get this capacity from Amazon. We proceeded to do the 341,700 hours of computational chemistry, or 39 compute years, against this protein target, and then shut it down.

So, 10,600 servers, 39 years of compute in 11 hours, on the equivalent of $44 Million in infrastructure, for only $4,362!

Simply put, Chef 11 Scales!
Now we know that the latest version of Chef, rewritten with an Erlang-PostgreSQL combo for scale, is supposedly faster/better than the Ruby-Couch version, but we just wanted to put it through its paces.

And it passed! Boy did it.  It was very cool when we ran knife, and saw:

Knife Output

 

Here’s the view from our CycleServer plug-ins, showing a heck of a lot of servers that had successfully converged:

Converged!

 

Lastly,  that’s a heck of a lot of servers running science. And you can see from our ganglia view that Cycle’s software has the cluster red hot and using 99% of the CPU:

Red hot science!

 

The future…
So there we have it, we just handled 10,600 servers, and our software built the environment, secured it, scheduled data across, scaled it, and tracked everything for audit/reporting purposes. Chef 11 handled configuration for all of them. But now we’re ready to add zeros here, and so is our software.

If you’ve got a scientific, engineering, or finance questions that need “more zeros”, we’d love to hear from you!

Or if you’re looking for a job, where you get to throw down world-class engineering, or you want to help our business grow, we’d also love to hear from you!

Right People, Right Place, Right Time - Cycle Hiring to meet explosive demand

Dear HPC, HTC, and Cloud communities,

We'd like your attention, please, for a moment. Cycle has had the good fortune to do some amazing things over the years, but now we've hit a serious growth curve, so we're delighted to say:

We're hiring. And not in a small way... Every month, every quarter, from here on out.

At Cycle we believe that many of the world’s scientific, engineering and finance minds are shackled by a lack of access to compute power.Our products connect people to computing resources at any scale, when it’s needed most. Many Fortune 500's, start-ups and public research customers use our software to run mission-critical science, risk management, and engineering, and now we're growing our team of game-changers. 

Cloud HPC/HTC and utility supercomputing are here, and we're leading that charge:

• We have a full product set, and we're rolling
• We're hiring, in many functions from engineering, sales, business development, operations, etc.  
• We're helping customers do amazing work, check out the coverage in Wired, the NY Times, BusinessWeek, or the Wall Street Journal.

So if you're an overachiever, if you want to be at a company helping the world fight disease, designing better/safer products, or ensuring returns for retirement funds that are decades in the making, then we want you. You're honest, you’re smart, you get things done, and you want to join a team at this 100% employee-owned software company.

So check out our current job listings, send an e-mail to jointheteam -at- cyclecomputing.com with the job title in the subject, and your resume. Come interview, show us your strengths in engineering, sales, business development, sales engineering, or operations, and make the world a better place in the process.

Let's get moving, these diseases won't just cure themselves...

Thanks,
The Cycle Team

 

Fortune 500s discuss Cloud HPC, Utility Supercomputing @ Cycle's re:Invent session

As many of you know, at Cycle we think that giving every researcher, scientist, engineer, and mathematician access to the compute power they need, exactly when they need it, will enable humanity to achieve what its truly capable of. 

So we organized five Fortune 500 Cycle customers of ours to talk at AWS re:Invent at 1pm Wednesday the 28th, about Cloud, HPC, and utility supercomputing.

Whether its building safer medical devices, managing risk, helping quantify genomes at scale, protect hard-earned retirement funds, or find medicines to cure disease, they'll be talking about how they use Cloud to do it!

At 1pm tomorrow (Wednesday) come to "Enterprise HPC in the Cloud: Fortune 500 use cases" in room 3401A to see:

• HartfordLIfe
• Johnson & Johnson
• Life Technologies 
• Novartis 
• PacificLife

If you can't make the session come to Cycle's Booth #220, and we can talk more there!

BigData, meet BigCompute: 1 Million Hours, 78 TB of genomic data analysis, in 1 week

It seems like every day at Cycle, we get to help people do amazing work, but this week is a little different. This week we wrapped up our involvement in the amazing work by Victor Ruotti of the Morgridge Institute for Research, winner of the inaugural Cycle Computing BigScience Challenge. In the name of improving the indexing of gene expression in differentiated stem cells, Cycle's utility supercomputing software just finished orchestrating the first publicly disclosed 1,000,000+ core hour HPC analysis on the Cloud. Yes, that’s 1 Million hours, or over a ComputeCentury^TM of work, on a total of 78 TB of genomic data, in a week, for $116/hr! 

To put this 115 years of computing into context, the word ‘computer,’ meaning an electronic calculation device, was first used in 1897. So if you had started this run on a one-core computer when the term was first used, and kept it running through World War I, Jazz, the roaring 20’s, the Great Depression, WWII, Big Bands, the start of Rock’n’Roll, the Cold War, the Space Race, the Vietnam War, Disco, the 80s, grunge, techno, hip hop, reality TV, and up to Gangnam Style, Victor’s analysis would be finishing now, sometime in 2012. Now that’s a lot of compute.

Below, we're going to explain the details of the analysis, and how it was executed, but if you're short on time, please skip to why this is important. 

Cycle Computing BigScience Challenge Overview

About a year ago we were very excited to announce the Challenge, a contest aimed at breaking the computation limits for any researchers working to answer questions that will help humanity. We asked researchers all over the world to think of normally unanswerable computational science questions, i.e. science that was limited by the compute power they had available,  describe their efforts and how access to a Utility Supercomputer could push their research forward, by making impossible science, possible.

As our part of the challenge, Cycle Computing offered $10,000 of compute time on a Utility Supercomputer, with Amazon Web Services kindly providing an additional $9,500 worth of compute time to the contest winner. From a field of many researchers doing fantastic work to benefit humanity, our panel of judges including industry luminaries such as Kevin Davies of Bio IT World, Peter Shenkin of Schrodinger, Jason Stowe of Cycle Computing, and Matt Wood of AWS, chose Alan Aspuru-Guzik of the Harvard University Chemistry department and the Harvard Green Energy Project as the Runner-up, and Victor Ruotti from Jamie Thomson’s Stem Cell Lab at the Morgridge Institute for Research as the BigScience 2011 challenge winner!

Victor required the massive computational power of a Utility Supercomputer to analyze gene expression data in order to construct a map of which genes are expressed when pluripotent stem cells differentiate, or turn into a specific cell type or state. His goal is accelerating the identification of cell types and the genes involved with creating them from induced pluripotent stem cells. More details on the phases of this analysis appear below:

Figure: Slide from Victor Ruotti on the phases of his research

To accomplish this goal, he ran a set of comparisons, in an n-squared algorithm, against 124 samples. Doing analysis on these 124x124 sample pairs, from a larger pool of 524x524, using bowtie to perform RNA Sequence analysis, is both compute and data intensive. The total data footprint, including intermediate data, was 78TB of storage, which was analyzed using 1,000,000 hours of computation. BigData, let us introduce you to BigCompute.

Figure: Running(green) and Idle(yellow) jobs for a portion of Victor's research

Sequence analysis also requires a large amount of memory, so we built our cluster mostly from high-memory Amazon EC2 instances (m2.xlarge, m2.2xlarge, and m2.4xlarge). To ensure we were able to do as much science as possible while staying in budget we used only Spot Instances, which at the time of the run were typically 12 times less expensive compared to on-demand instances.

Instance Type	On-Demand Price / Hour	Approx. Spot Price / Hour
m2.xlarge	$0.45	$0.037
m2.2xlarge	$0.90	$0.075
m2.4xlarge	$1.80	$0.15

In the end, we are pleased to announce that the BigScience 2011 workload is the first publicly discussed 1,000,000+ core-hour HPC run on cloud. For this run, CycleCloud helped:

• Create one-click massive clusters in the cloud
• Route jobs, input and result data
• Handle the common cloud failure conditions
• Automatically adjust the cluster size to fit the workload
• Provision thousands of instances scheduled with HTCondor, which the Morgridge Institute for Research selected to best meet their needs, (other options on CycleCloud clusters include GridEngine, Torque, etc.), and 
• Configure the nodes' software, which Cycle's software uses Opscode Chef

Figure: CycleServer's visualization of Opscode's Chef working smoothly on thousands of hosts

We were able to start this multi-thousand core cluster in under 20 minutes. This cluster was used to do about 115 compute years of analysis in about 7 days against 78 TB of genomic data! It ran an average of about 5,000 cores 24/7, with a peak of over 8,000 cores. How much does a million hours of compute and 78 TB of storage cost? Well, we had a budget and in the end it ended up costing a mere $116/hour or $19,555 total! And if anyone wants to run big RNASeq, we can spin this up easily, any time.

Figure: Ganglia data showing a hot (yellow) cluster with thousands of hosts!

Why this is important: how this innovative work benefits us all

Now Victor has the data and will start compiling the first part of his indexing system of the cells, which will allow researchers to quickly classify the cells based on their expression pattern and identify genes and regions of the genome that are critical for establishing cell states that have potential for clinical applications. Ideally it should radically accelerate researchers using stem cells to replicate diseases in the petri dish, to enable easier experimentation for potential treatments. Wow!

We’re very excited about the results of the first CycleCloud BigScience Challenge, and that it helped Victor to think big, to tackle the impossibly large questions that should be asked, and to use the power of utility supercomputing to answer them. We’d like to thank AWS for joining us in sponsoring this research. And finally, Cycle Computing, AWS, and the Judges congratulate Victor Ruotti for his breakthrough work in the field of stem cell research, for helping push humanity forward by using over a ComputeCentury^TM of analysis to make impossible BigScience possible!

Last but not least... Cycle Computing BigScience Challenge 2012

Finally, as it’s getting to be that time of year again, get your creative juices flowing and start thinking BIG because this year’s Cycle Computing BigScience Challenge is here! If you’re interested in applying to run research that will help humanity, go to our Cycle Computing BigScience Challenge page and fill in an entry with who you are, what your big question is, why it needs BigCompute and/or BigData to make it happen, and how it benefits humanity. This year, anyone, in a non-profit or for-profit organization, can apply, and we can't wait to see how you all plan to change your work, your science, and hopefully the world.

Free Grill v1.5 and Grill Recipe Challenge announced!

We’re pleased to announce the release of Grill version 1.5 for Opscode Chef! And it’s FREE!

We’ve added a few features that came in useful during our last Utility Supercomputing run code-named Naga, including:

• New customizable reports
• Backporting Chef alert system to CycleServer core
• Greatly improved performance for large data sets
• Hosts are now removed after a certain amount of inactivity

But we have a dirty secret: we don’t have a publicly available cookbook to install it.

We know, we know. We wrote a chef report visualization tool that can handle several thousand nodes all converging at once but we don’t have an installer cookbook.

Well, we do actually have an installer, but it’s tightly-coupled to CycleCloud and we just haven’t had time to make a rock-solid generally-useful cookbook.

So we’d like to announce the Grill Recipe Challenge. Write an awesome Grill cookbook and we’ll send you a CycleComputing Mug and T-shirt. Here’s the simple rules:

1. Submit your cookbook to grill-recipe@cyclecomputing.com
2. Release your cookbook under the Apache license. 
3. We’ll accept entries until 11:59 PM PST on June 12th 2012. 
4. We’ll pick the best one and send the winner a sweet Cycle mug and T-shirt 
5. (our decisions are final! ;)

So if you need to explore Chef converge data, download Grill today, kick the tires, write an awesome cookbook, and win fabulous prizes... :D

CycleCloud Achieves Ludicrous Speed! (Utility Supercomputing with 50,000-cores)

Update: Since publishing this blog entry, our 50,000 core CycleCloud utility supercomputer has gotten great coverage by BusinessWeek, TheRegister, the NY Times, the Wall Street Journal’s CIO Report, Ars Technica, TheVerge, among many others. And now it would run for $750/hr with the AWS spot pricing as of 6/22/2012! Click here to contact us for more information...

By now, we've shown that our software is capable of spinning up cloud computing environments that run  at massive scale and produce real scientific results.  After some of our previous efforts, we realized we were onto something with the CycleCloud Cloud HPC and Utility Supercomputing concept. However, even we underestimated the scales researchers would want to use and the scope of the research that this would impact. 

Among the requests were some from a leader in computational chemistry research, Schrodinger. In collaboration with Nimbus Discovery, they needed to virtually screen 21 million molecule conformations, more than ever before, against one possible cancer target using their leading docking application, Glide. And they wanted to do it using a higher accuracy mode early-on in the process, which wasn’t possible before because it is so compute intensive!

This is exactly what we did with our latest 50,000 core utility supercomputer that CycleCloud provisioned on Amazon Web Services, code-named Naga.  And Schrodinger/Nimbus got useful results they wouldn't have seen without utility supercomputing. We will describe how we accomplished this below, and in future articles and future blog posts.

From a scale perspective, the most revolutionary concept implemented for Naga was scaling out all the components of an HPC environment. In our previous megaclusters, we performed a great deal of optimization to scale one scheduler to handle as many cores (slots) as possible. With Naga, it was clear that we needed to scale out multiple aspects of the system so we could use capacity wherever we found it.

We ran Naga across each of the 7 regions that AWS currently supports, scaling-out all supporting systems of a cluster (scheduling, software configuration, etc.) so we could use idle capacity wherever we found it. However, the magic really happened when we layered CycleServer on top of Naga and allowed our revolutionary new job submission algorithm to intelligently dole out work to each region based on real-time measurements from that region. Using this architecture, we had built ourselves a secured, automated 50,000 core supercomputer in under two hours using AWS infrastructure.

The amazing thing about this cluster was that it was launched via CycleCloud by the enduser and the jobs were submitted to the cluster through CycleServer by the enduser as well. All of the automation work that went into the Naga megacluster means that Cycle engineers largely got to sit back and monitor the progress of the workload as it progressed.

Here are the cold hard stats:

Resource	Count
Total Instances	6742
- c1.xlarge instances	5,435
- c1.medium instances	779
- cc1.4xlarge instances	297
- cc2.8xlarge instance	231
cores	51,132
RAM	58.78-TB
AWS Regions	All (7: us-east, us-west1, us-west2, eu-west, sa-east, ap-northeast, ap-southeast )

Here is a map of the compute resources harnessed during the Naga run:

Here is an analysis of the staggering amount of compute power that Naga provided:

Metric	Count
Compute Hours of Work	109,927 hours
Compute Days of Work	4,580 days
Compute Years of Work	12.55 years
Ligand Count	~21 million ligands

 

THE REAL IMPORTANT NUMBERS!

The most important thing about this run are the following two numbers:
Time to run the impossible science: ~3 hours
Cost at peak: $4828.85/hour!

You read that right, 20+ million dollars of infrastructure was used for $4,828 per hour. Wow!

As always, we used a large suite of CycleServer visualizations to monitor the run.  These include CycleCloud compute provisioning, Condor job scheduling visualizations, OS-level performance statistics, CycleServer-Grill to monitor OpsCode Chef, and others that we’ll be talking about in the coming weeks.  Here is a sampling of some of the dashboards we were monitoring in real time:

As you can see, Cyclecloud was able to launch an outrageous number of machines in AWS, our Chef environment converged all of them into useful workers, CycleServer was able to dole out jobs to Condor schedulers, the Condor schedulers were able to quickly fill the compute resources with jobs, and we were able to monitor the overall utilization of all 50,000 cores working in unison.  

 

THE RESULTS

 

As part of this run, Schrodinger, in collaboration with Nimbus Discovery, has already identified compounds they would not have seen if it weren't for CycleCloud Utility Supercomputing! Now they're acquiring the compounds, and will be testing them in the lab. 

And all of this was possible by under $5000 an hour in AWS fees. We’re talking about a supercomputer that would cost tens of millions of dollars to purchase, power, cool, and maintain. If that isn’t a transformational capability, we don’t know what is! 

 

There is no industry that won’t be impacted by this technology, from insurance to life science, manufacturing to computer-aided product design, aerospace to energy. So, if you have a big problem that you’d like to solve in a few hours instead of a few years, give us a call. If you don’t currently have a big problem, sit back and think about what big problems face your organization that could really move it forward, but you might never ask because it would take too much computation. It’s time to think about research differently. We’d love to introduce you to Utility Supercomputing using CycleCloud.