Cycle Computing Orchestrates Cancer Research on Google Cloud

By Tiffany Trader

September 10, 2015

This week HPC cloud software specialist Cycle Computing announced that its full suite of products can now be used to spin up clusters on Google’s cloud platform. As testament to the new partnership, Cycle leveraged Google Compute Engine (GCE) to run a 50,000-core cancer gene analysis workload for the Broad Institute.

As Cycle Computing explains, Broad’s Cancer Group approached them with the need to perform a highly-complex genome analysis. The researchers already had powerful processing systems in-house, but running the analysis would take months and would require extensive coordination.

The decision was made to utilize the newly-launched “preemptible virtual machine” instances on GCE to further their cancer research. Preemptible VMs are Google’s answer to competitor Amazon’s spot instances. The preemptible instances are 60-70 percent cheaper than their on-demand counterparts. The catch is that Compute Engine can terminate (preempt) these instances at any time and there are a finite number available.

For applications that are “interruption friendly” (aka fault-tolerant), preemptible VMs offer a nice discount, and as Cycle explains, its software handles resiliency, enabling the orchestration of “clustered applications at any scale.”

Both classic “big compute” jobs as well as batch processing jobs can run on preemptible instances. If some instances terminate during processing, the job slows but does not completely stop.

Cycle expects the following applications will stand to benefit from preemptible VMs:

  • Computational chemistry
  • Needle-in-a-haystack simulations
  • Financial pricing, back testing, modeling
  • Genomics, bioinformatics, proteomics
  • Insurance risk management
  • Rendering, media encoding
  • Hadoop, Spark, Redis, other IoT processing frameworks

Enabling greater access to utility-scale computing has always been the primary mission of Cycle Computing. The company has until now relied solely on Amazon’s cloud cycles, but by expanding its partner ecosystem it can better match and meet its customer needs. Recall that Broad and Google were already collaborating to develop new tools to facilitate and propel biomedical research. And in June, Broad Institute’s Genome Analysis Toolkit, or GATK, became available on Google Cloud Platform, as part of Google Genomics.

Cycle CEO Jason Stowe said Cycle doesn’t one recommend vendor over another, and that the applications cited are also well suited for AWS spot instances. “We provide tools that allow companies to benchmark their workloads on differing infrastructure and to be able to run them in production quality fashion; we stay out selection decisions. We obviously tell customers the options they have but we follow the customer.”

In general, he said, “Throughput-oriented stateless workloads tend to work well on that type of infrastructure and are definitely able to run on both Google GCE preemptible VMs and AWS spot instances.” The costs benefits can be substantial.

Broad’s Cancer Program has data sets pertaining to hundreds of cancer cell lines with information about genetic mutations, gene expression, and molecular interaction. Each level of data is massive in its own right, but exposing the hidden connections between these layers requires a comprehensive analysis. These relationships act as signposts directing the Cancer Program toward future research endeavors.

The scale of Broad’s scientific workload was not unfamiliar to Cycle, a company that prides itself on inspiring researchers to ask the “big questions” without regard to the limits of computing power. As Cycle describes it, this was a project that was at risk of not going forward if limited to available local resources.

“These types of analyses provide the clues that can lead to breakthroughs in disease research, such as cancer research, and this kind of cloud-based infrastructure helps us remove some of the local computing barriers that can stand in the way,” said Chris Dwan, acting director of information technology at the Broad Institute. “Flexible processing power allows us to think on a much larger scale.”

Revealing this map requires compute-intensive machine learning algorithms, the kind that would take months to execute on Broad’s on-premise system. The researchers already had the workload set up to run on an existing cloud-based StarCluster framework, so the challenge was to get this working on Google.

Cycle connected its CycleCloud to Google Cloud Platform, and ensured that its workload placement, data schedule, and at-scale computing capabilities were available on Google. Cycle says they were able to get this job up and running at moderate scales in 90 minutes using Cycle’s automation and orchestration tools as well as their cluster containers.

“The porting process for CycleCloud was very easy to accomplish. We were even able to simplify some of our existing code, because Google features like per-minute billing mean that we don’t have to worry about optimizing usage for hourly charges,” said Rob Futrick, chief technology officer for Cycle Computing.

Finding that the application hit its scaling sweet spot at about 50,000 cores, the Cycle team set the cluster to autoscale to 51,200 cores, requiring 3,210 16-core instances, using a mix of both n1-highmem and n1-standard types. Provisioned for less than the cost of a single server, this petascale cluster enabled Broad’s Cancer Group to complete their mapping workload in one afternoon. And as it so happens, some of the instances were preempted, but CycleCloud automatically reconfigured the cluster sans nodes, so the jobs continued.

After about six hours of computation, Broad’s map was complete. Analysis and curation will reveal the full extent of the relationships that were uncovered.

Cycle-Google-Preemptible-Instances-51200-core-CycleCloud-Cluster

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a community infrastructure in support of machine learning research Read more…

By John Russell

DARPA Continues Investment in Post-Moore’s Technologies

July 24, 2017

The U.S. military long ago ceded dominance in electronics innovation to Silicon Valley, the DoD-backed powerhouse that has driven microelectronic generation for decades. With Moore's Law clearly running out of steam, the Read more…

By George Leopold

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in 2017 with scale-up production for enterprise datacenters and Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

Trinity Supercomputer’s Haswell and KNL Partitions Are Merged

July 19, 2017

Trinity supercomputer’s two partitions – one based on Intel Xeon Haswell processors and the other on Xeon Phi Knights Landing – have been fully integrated are now available for use on classified work in the Nationa Read more…

By HPCwire Staff

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provid Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic Read more…

By Doug Black

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This