CycleCloud BigScience Challenge Boosts Stem Cell Research

By Tiffany Trader

March 13, 2012

Cycle Computing has proclaimed the winner of the 2011 CycleCloud BigScience Challenge. Victor Ruotti, a computational biologist at the Morgridge Institute for Research, will receive $10,000 in credit from Cycle Computing and four hours of CycleCloud engineering support, plus an additional $2,500 in credit from Amazon Web Services. The award will be used for cutting-edge stem cell research.

The Challenge, which was revealed in detail at the SC11 conference, was open to non-profit researchers who could harness the power of utility supercomputing to answer big science questions that have the potential to offer real benefits to humanity. The results are being announced after a careful evaluation of the five finalists. HPC in the Cloud spoke with Cycle Computing CEO Jason Stowe and the winning finalist, Victor Ruotti, to learn more.

Located on the campus of the University of Wisconsin-Madison, the Morgridge Institute for Research is a private, not-for-profit interdisciplinary biomedical research organization that seeks to accelerate the movement of science from the laboratory to the clinic. Ruotti works in the Thomson Laboratory, run by stem cell pioneer James A. Thomson. Thomson was part of a team that first transformed adult cells into stem cells called iPS cells in 2007. This was a huge breakthrough and has had a significant impact on science and medicine in the years since.

Ruotti’s research group is working on developing a knowledge base indexing system for human embryonic stem cells and their derivatives. The science is based on a fascinating regenerative process called dedifferentiation, which allows the researchers to take an adult cell and turn it into a human embryonic cell, and then further transform that into different cell types.

“You start with a cell and treat it with a certain differentiation factor and these cells which are human embryonic stem cells turn into a particular cell. This is a very complicated process because sometimes we don’t know what cell type they are turning into,” says Ruotti.

He explains this requires RNA sequencing to find more information based on genetic markers and morphology using 3-dimensional pictures. But still it’s difficult to tell what cells they are turning into. After performing over 1,000 different RNA sequences, Ruotti came up with the idea of creating a sort of dictionary to assist in the identification of cell types. This knowledge base indexing system will provide a percent probability that a certain cell is neural, or cardiac, or smooth muscle, or any other cell. The work they are doing now is laying the foundation for their ultimate goal, which is enabling advances in real-world regenerative biology.

Stowe chimes in: “The thing that got us excited about Victor’s work is the huge potential of the knowledge base that he’s putting together. It says if I start out with an undifferentiated cell and want it to end up in a particular direction, here are the probabilities for that to happen. But the primary blocker here in terms of doing the analysis is raw compute horse power. Taking advantage of a really large numbers of compute hours, a quarter million computer hours should really benefit his research.”

When Ruotti initially went to lab founder James Thomson with a detailed explanation of the knowledge base proposal, he was met with raised eyebrows: “You can do that?” Thomson asked?

“We can if we get this number of compute nodes,” replied Ruotti.

“Oh, great! Then do that,” Ruotti recalls Thomson telling him.

The basis of their research is identifying the differentiated cells, but to do this, the team must first perform a series of very computationally-intensive analyses. The science was hinging on the computational power. This is exactly the kind of project Cycle CEO Jason Stowe had in mind when he formulated the BigScience Challenge.

“There are a huge number of potential clinical applications for helping people build treatments based on differentiated cells. It’s a great fit, answering the big questions that couldn’t be answered without utility supercomputing,” says Stowe.

In addition to the grand prize winner, the contest judges selected a final runner-up, Alan Aspuru-Guzik, from the Harvard Clean Energy Project, for his material science analysis aimed at creating more efficient photo-voltaic cells.

All finalists were awarded both an initial $500 credit from Cycle Computing and an additional $1,000 credit from Amazon Web Services (AWS). Aspuru-Guzik, as the runner-up, will also receive access to some of the idle capacity that Cycle generates as part of executing and building its software.

The top projects were selected based on their creativity, benefit to society and on the appropriateness of a running their workloads on Cycle clusters in the AWS cloud. In addition to the top two choices, there were three other finalists in the pool: Jesus Izaguirre from the University of Notre Dame (diabetes research); Soumya Ray from Harvard Medical School (Parkinson’s research); and Martin Steinegger from TU Munich ROSTLAB (mapping genomic diversity). Tasked with having to sort through all these worthy candidates were judges Jason Stowe, CEO, Cycle Computing; Kevin Davies, editor-in-chief, Bio-IT World; Matt Wood, technology evangelist for Amazon Web Services; and Peter S. Shenkin, vice president, Schrödinger.

The next step, according to Stowe, will be to connect Ruotti with Cycle engineers to give them a better idea of the specific workloads and the technical requirements. Then it will be up to Ruotti and his team from an execution standpoint. The other finalists will also be given the chance to advance their research with the awards they received, and HPC in the Cloud will be sure to report on future findings.

Subscribe to HPCwire's Weekly Update!

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

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire