Cloud Computing Will Usher in a New Era of Science Discovery

By Gilad Shainer, Brian Sparks, Scot Schultz, Eric Lantz, William Liu, Tong Liu, and Goldi Misra

January 26, 2010

Computational science is the field of study concerned with constructing mathematical models and numerical techniques that represent scientific, social scientific or engineering problems and employing these models on computers, or clusters of computers to analyze, explore or solve these models. Numerical simulation enables the study of complex phenomena that would be too expensive or dangerous to study by direct experimentation. The quest for ever-higher levels of detail and realism in such simulations requires enormous computational capacity, and has provided the impetus for breakthroughs in computer algorithms and architectures.

Due to these advances, computational scientists and engineers can now solve large-scale problems that were once thought intractable by creating the related models and simulate them via high performance compute clusters or supercomputers. Simulation is being used as an integral part of the manufacturing, design and decision-making processes, and as a fundamental tool for scientific research. Problems where high performance simulation play a pivotal role include for example weather and climate prediction, nuclear and energy research, simulation and design of vehicles and aircrafts, electronic design automation, astrophysics, quantum mechanics, biology, computational chemistry and more.

Computation is commonly considered the third mode of science, where the previous modes or paradigms were experimentation/observation and theory. In the past, science was performed by observing evidence of natural or social phenomena, recording measurable data related to the observations, and analyzing this information to construct theoretical explanations of how things work. With the introduction of high performance supercomputers, the methods of scientific research could include mathematical models and simulation of phenomenon that are too expensive or beyond our experiment’s reach. With the advent of cloud computing, a fourth mode of science is on the horizon.

The concept of computing “in a cloud” is typically referred as a hosted computational environment (could be local or remote) that can provide elastic compute and storage services for users per demand. Therefore the current usage model of cloud environments is aimed at computational science. But future clouds can serve as environments for distributed science to allow researchers and engineers to share their data with their peers around the globe and allow expensive achieved results to be utilized for more research projects and scientific discoveries.

To allow the shift to the fourth mode of “science discovery,” cloud environments will need not only to provide capability to share the data created by the computational science and the various observations results, but also to be able to provide cost-effective high performance computing capabilities, similar to that of today’s leading supercomputers, in order to be able to rapidly and effectively analyze the data flood. Moreover, an important criteria of clouds need to be fast provisioning of the cloud resources, both compute and storage, in order to service many users, many different analysis and be able to suspend tasks and bring them back to life in a fast manner. Reliability is another concern, and clouds need to be able to be “self healing” clouds where failing components can be replaced by spares or on-demand resources to guarantee constant access and resource availability.

The use of grids for scientific computing has become successful in the fast years and many international projects led to the establishment of worldwide infrastructures available for computational science. The Open Science Grid provides support for data-intensive research for different disciplines such as biology, chemistry, particle physics, and geographic information systems. Enabling Grid for ESciencE (EGEE) is an initiative funded by the European Commission that connects more than 91 institutions in Europe, Asia, and United States of America, to construct the largest multi-science computing grid infrastructure of the world. TeraGrid is an NSF funded project that provides scientists with a large computing infrastructure built on top of resources at nine resource provider partner sites. It is used by 4000 users at over 200 universities that advance research in molecular bioscience, ocean science, earth science, mathematics, neuroscience, design and manufacturing, and other disciplines. While grids can provide a good infrastructure for shared science and data analysis, several issues make the grids problematic to lead the fourth mode of science — limited software flexibility, applications typically need to be pre-packaged, non elasticity and lack of virtualization. Those missing items can be delivered through cloud computing.

Cloud computing addresses many of the aforementioned problems by means of virtualization technologies, which provide the ability to scale up and down the computing infrastructure according to given requirements. By using cloud-based technologies scientists can have easy access to large distributed infrastructures and completely customize their execution environment. Furthermore, effective provisioning can support many more activities and suspend or bring to life activities in an instant. This makes the spectrum of options available to scientists wide enough to cover any specific need for their research.

In many scientific fields of studies, the instruments are extremely expensive, and as such, the data must be shared. With this data explosion and as high performance systems become a commodity infrastructure, the pressure to share scientific data is increasing. That resonates well with the emerging cloud computing trend. While for the moment cloud computing appears to be a cost effective alternative for IT spending, or the shift of enterprise IT centers from capital expense to operational expense, research institutes have started exploring how cloud computing can create the desired compute centralization and an environment for researchers to chare and crunch the flood of data. One example is the new system at the National Energy Research Scientific Computing Center (US), named “Magellan.” While Magellan’s initial target is to provide a tool for computational science in a cloud environment, it can be easily modified to become a center for data processing accessed by many researchers and scientists

Until recently, high performance computing has not been a good candidate for cloud computing due to its requirement for tight integration between server nodes via low-latency interconnects. The performance overhead associated with host virtualization, a prerequisite technology for migrating local applications to the cloud, quickly erodes application scalability and efficiency in an HPC context. The new virtualization solutions such as KVM and XEN aim to solve the performance issue by allowing native performance capabilities from the virtual machines by reducing the virtualization management overhead and by allowing direct access from the virtual machines to the network.

High-speed networking is a critical requirement for affordable high performance computing, as clusters of servers and storage need to be able to communicate as fast as possible between them. A vast majority of the world top 100 supercomputers are using the high-speed InfiniBand networking due to this reason, and the interconnect allows those systems to reach to more than 90 percent efficiency, a critical element for effective for high performance computing in any infrastructure, including clouds. National Energy Research Scientific Computing Center (NERSC, US) “Magellan” system is using InfiniBand as the interconnect to provide the fastest connection between servers and storage in order to allow the maximum gain from the system, highest efficiency and an infrastructure that will be able to analyze data in real time.

Power consumption is another important issue for high performance clouds. As the HPC clouds become bigger, affordability of science discovery will be determined by the ability so the save the costs of the power and cooling. Power management, which is implemented within the CPUs, the interconnect and the system management and scheduling will need to be integrated as a comprehensive solution. Non utilized sections of the clouds need to be powered off or moved into power saving states and the scheduling mechanism will need to incorporate topology awareness.

The HPC Advisory Council HPC|Cloud group is working to investigate the creation and usage models of clouds in HPC. Past activities on smart scheduling mechanisms have been published on the council’s Web site, and future results will include the usage of KVM and XEN, manycore CPUs (such as AMD’s Magny-Cours which includes 12 cores in a single CPU) and cloud management software (such as Platform ISF) will be published throughout 2010. The HPC Advisory Council will continue to investigate the emerging technologies and aspects that will lead us into the fourth mode of science.

Acknowledgments

The authors would like to thank Cydney Stevens for her vision and guidance.

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!

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

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

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Quantum Adds Global Smarts to StorNext File System

April 20, 2017

Companies that use Quantum’s StorNext platform to store massive amounts of data this week got a glimpse of new storage capabilities that should make it easier to access their data horde from anywhere in the world. Read more…

By Alex Woodie

Scaling an HPC Career in Nepal Can Be a Steep Climb

April 20, 2017

Umesh Upadhyaya works as an IT Associate at the International Centre for Integrated Mountain Development (ICIMOD) in Nepal, which supports the country’s one and only HPC facility. He is directly involved in an initiative that focuses on climate change and atmosphere modeling Read more…

By Nages Sieslack

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Intel Open Sources All Lustre Work, Brent Gorda Exits

April 19, 2017

In a letter to the Lustre community posted on the Intel website, Vice President of Intel's Data Center Group Trish Damkroger writes that effective immediately the company will be contributing all Lustre development to the open source community. Damkroger also announced that Brent Gorda, General Manager, High Performance Data Division at Intel is leaving the company. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Penguin Takes a Run at the Big Cloud Providers

April 12, 2017

HPC specialist Penguin Computing recently re-ran benchmarks from a study of its larger brethren and says the results show its ‘public cloud’ – Penguin on Demand (POD) – is among the leaders in cost and performance. Read more…

By John Russell

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

HPC and the Colocation Datacenter – a Bridge Too Far?

April 7, 2017

A more standardised HPC platform approach is making the running of HPC projects within increasing financial reach. Read more…

By Clive Longbottom, Quocirca

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 phase of neural networks (NN). 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. Read more…

By John Russell

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 campaign. 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 assets. 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

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. 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

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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