San Diego Supercomputer Center “Seeds” HPC Clouds

By Amit Chourasia, Jan Zverina, SDSC

June 18, 2014

All sectors of the high-performance computing community – academia, industry, and government – have long been in need of an infrastructure that allows researchers to easily share their findings with other scientists or organizations in an efficient and secure manner.

Sharing these results are of vital importance because they form the basis for validation and potential next steps in any research project, from cosmology to genome sequencing. Computational visualizations and simulations, for example, have become an indispensable resource across numerous science domains. But while quick and effective assessments of such data are necessary for efficient use of the computational resources involved, such an exercise can be challenging when a research team is large and/or geographically dispersed, or some members don’t have direct access to an HPC system.

Moreover, current methods for sharing and assessing results, can be labor-intensive and unsupported by useful tools and procedures. Typically, a research team must create their own scripts and ad hoc procedures just to move results from system to system or user to user. These efforts usually rely on email, ftp, or secure copy (scp) despite the ubiquity of more flexible web-based technologies, and do not fully take advantage of the interactive capabilities of today’s mobile devices.

In late 2012 the San Diego Supercomputer Center (SDSC) at the University of California, San Diego, was awarded a three-year, $810,000 grant from the National Science Foundation to develop a resource that lets researchers seamlessly share and stream scientific visualizations on a variety of platforms, including mobile devices. Called SeedMe for ‘Swiftly Encode, Explore, Disseminate My Experiments’, SDSC’s web-based architecture is designed to enable rapid sharing of content directly from applications running on HPC- or cloud-based resources.

This spring, a team of SDSC researchers developed a working implementation, which in addition to visualizations videos supports other content such as plots, files, and tickers – all of which are essential to scientific research. Easy-to-use programmatic and command line tools with documentation are available for end users to interact with SeedMe.org. A quick start guide, geared for HPC researchers, is also available.

“SeedMe now provides an essential yet missing component in current high-performance computing,” said Amit Chourasia, a senior visualization scientist at SDSC and principal investigator for the project. “We’re now inviting researchers from industry and academia and across numerous domains to take advantage of SeedMe’s easy-to-use functionality for sharing their results with peers or the public at large.”

“The current HPC infrastructure relies heavily on controlled access,” said Michael Norman, SDSC’s director and co-principal investigator for the project. “SeedMe provides secure input and public output complementing HPC resources without compromising their security model. We believe this project will have a transformative impact throughout numerous domains, as research has become increasingly collaborative, requiring better tools and resources that aid the sharing of information.”

seedme1

SeedMe User Interaction Sequence. Source, Amit Chourasia/SDSC

SeedMe is unique from other web-based interfaces in that it is completely focused on efficiently sharing scientific content. While SeedMe could be described in general terms as a DropBox for science, the computational research community requires several additional capabilities and integration tools.

“One such requirement is easy instrumentation of simulation codes, as well as support for instrumenting analysis routines from a variety of software tools,” said Chourasia. “That instrumentation may provide periodic tracking and monitoring by posting progress messages, job status, early data snippets, scripts, parameter files, and other reusable components. But no single web service or tool suite addresses the breadth of scientific computing challenges as effectively and easily as the SeedMe infrastructure.”

According to Chourasia, some of the most common complaints among researchers when needing to share results with colleagues include the fact that many simply cannot afford to spend time and valuable funding dollars to create their own system for sharing their results. “Many find that it is cumbersome or costly. They also don’t want to waste time searching email attachments, or constantly have to check files to monitor progress, or spend long hours encoding videos from a set of images to work on all devices.”

Toward that end, the objective of SeedMe is to foster rapid assessment, iteration, communication, and dissemination of research by making that research ubiquitously accessible on any device, including mobile ones, and on a near real-time basis. Results can be shared within private groups only or posted for public consumption, depending on user preferences.

“SeedMe aims to fill the automation and accessibility gap in computational research,” said Chourasia, noting that a core focus of the project is to promote accessibility of preliminary, ad hoc, and ephemeral content – all vital to efficient and successful research.

Visualization Speed-ups

Visualizations and simulations are an ever growing part of today’s scientific research. These state-of-the-art simulations are now creating visualization images at runtime using in-situ processing. Images or sequence of images can now be shared with others using SeedMe with simple asynchronous integration providing an easy monitoring and assessment mechanism for collaborators.

SeedMe also capitalizes on recent strides in video standardization across web-based communities, providing a significant speed-up in video encoding by using parallel-distributed processing, which is not possible on existing HPC platforms due to lack of state-of-the-art video compression tools on Linux-like operating systems.

seed3

Left: An image from a sequence of volume rendering of steam from volcano eruption simulation. A corresponding video created from the image sequence on left at desired frame rate provided by user. The videos are encoded at various resolutions (including native resolution) and are available for playback and download. Source Amit Chourasia / Darcy Ogden, UC San Diego

Right: An image from computation and visualization of Mandelbrot set. Here the computation and visualization are done in-situ and the images are uploaded to SeedMe asynchronously. Source: Brad Whitlock, Intelligent Light and Amit Chourasia, UC San Diego

“Our goal has been to convert a manual, serial, error-prone process into an automatic, easy-to-use streamlined, parallel and web accessible cyberinfrastructure, and at the same time create videos that are not only encoded at very high quality to mitigate compression artifacts for scientific content, but also make these easily downloadable for researchers” said Chourasia.

Early users are welcoming SeedMe. “It is so convenient to share research results with collaborators, compared with sending results through emails,” said Hao Xu, a post-doctoral researcher who has been running simulations about the evolution of galaxies on the Blue Waters supercomputer at National Center for Supercomputing Applications (NCSA).

“SeedMe provides convenient ways to organize results, which can be easily updated, making sure collaborators or new collaborators all see the most recent results,” said Xu, who has been working with SDSC Director Norman, an astrophysicist by training. “It also avoids the pain of finding figures and plots in emails, and is even proving to be a very useful resource during conference calls.”

Going forward, the SeedMe research team will explore the possibility of making the resource a platform for sharing reusable content. NCSA researcher Matthew Turk is currently investigating how best to share IPython Notebooks from yt software, which is used to analyze and visualize datasets from astrophysical simulations, nuclear engineering, and radio telescope data.

“By building in support to yt for uploading directly to SeedMe, we hope to enable faster, easier, and more seamless sharing of results for anyone using yt,” said Turk. “SeedMe also allows easy control over sharing permissions, while providing an easy-to-use interface for uploading images and data to a central location.”

Tutorials Planned

As an open, web-accessible and searchable research archive, SeedMe also is suitable for education and outreach programs. In addition to organizing tutorials, talks, and webinars to train new users and receive user feedback, the program will provide internships to high school and undergraduate students enabling them to learn about web technologies and the diverse range of research, while at the same time support monitoring of content on the project website.

Tutorials and workshops are already in the works, with presentations planned for XSEDE14 and SC14, as well as a webinar as part of SDSC’s Industry Partners program on July 24. Such sessions will show potential users how they can accomplish the following on personal computers and mobile devices directly from compute jobs.

  • Get fast feedback on compute jobs
  • Share that feedback rapidly with collaborators across the globe
  • Provide access to preliminary results to guide further job submission
  • Support discussion of feedback and results among collaborators.

Author Information

Amit Chourasia, 858 822-3656 or [email protected]

Jan Zverina, SDSC Communications, 858 534-5111 or [email protected]

Warren R. Froelich, SDSC Communications, 858 822-3622 or [email protected]

Complete details of the SeedMe project can be found at http://www.seedme.org/. The NSF award number for the SeedMe project is OCI-1235505. In addition to Chourasia and Norman, the SeedMe project team includes Mona Wong-Barnum, David Nadeau, and Andrew Ferbert, all with SDSC.

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