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The IBM-built Pegasus (2) supercomputer came online in spring 2013, offering UM researchers the ability to perform 160 trillion floating-point operations per second. Housed at the Equinix NAP of the Americas data center in Miami, it features a new generation of Intel central processing units, making it five times faster and more powerful than the previous Pegasus introduced in 2010. Intel made the new state-of-the-art processing units, called Phi, available only to UM and a handful of other institutions.

The system is more powerful than its predecessor. It joins a family of systems making the environment one of the largest centralized academic cyber infrastructures in the country. The Pegasus (2) was ranked at number 389 on the November 2012 Top 500 Supercomputer Sites list.

Please contact hpc@ccs.miami.edu with any questions.

Pegasus Specs

Pegasus’ CPU Workhorse—The IBM iDataPlex dx360M4

Compute Nodes 350 dx360 M4 Compute Nodes
Processor Two 8-core Intel Sandy Bridge 2.6 GHz scalar, 2.33 GHz* AVX
Memory 32 GiB (2 GiB/core) using eight x 4GB 1600MHz DDR3 DIMMs
Clustering Network One FDR InifiniBand HCA
Management Network GB Ethernet NIC connected to the cluster management VLANs. IMM access shared through the eth0 port

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Sample Projects Run on Pegasus

Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) Project  | Project Leader: Tamay Ozgokmen
Fund Title:  Consortium for Advanced Research on Transport of Hydrocarbon in the Environment
Fund Source:  Gulf of Mexico Research Initiative
CPU Hours: 5,000,000  | IDSC Focus Area:  Earth Systems
Scientific Justification: Building on results from RFP-I, CARTHE remain focused on advancing fundamental understanding and modeling of the diverse physical mechanisms responsible for hydrocarbon transport in the Gulf of Mexico environment. An integral part of any informed response to a future event like the Deepwater Horizon incident requires knowledge of the distribution of pollutants in the water column and the ability to predict where and how fast the pollutants will spread. This information is also crucial for estimating the pollutants’ impact on the local ecosystem and coastal communities. The overall goal of CARTHE is accurate predictive modeling of pollutant transport from ocean-bottom release to landfall on the beach.  This project specifically identifies two topics, whose understanding is critical for oil spill dispersion prediction; namely (i) the dynamics of transport in the near-surface ocean and lower atmosphere, and (ii) transport in deep-ocean plumes.  Read more.

Age-Related Macular Degeneration (AMD) | Project Leader: William Scott
Fund Title:  Genomic Architecture of Progression and Treatment Response in AMD8
Fund Source:  National Institutes of Health (NIH) funded project EY012118
CPU Hours: 1,000,000  | IDSC Focus Area:  Bioinformatics + Health
Scientific Justification:  Age-related macular degeneration (AMD) is a significant health problem that affects millions of individuals and is the most common cause of severe vision loss among individuals over age 50 in the U.S. The influence of genetic variation on AMD is strong and through the application of recent technological advances the genetic etiology of risk for AMD is being deconstructed. Independent studies, including our own, have identified and confirmed variations in multiple genes that affect risk to AMD, including CFH, HTRA1/ARMS2, C2/CFB, and C3. Variation in these genes explain a significant portion of the genetic risk for AMD and ongoing studies are continuing to identify additional such genes. Also important are environmental risk factors such as smoking, hormone therapy and diet that contribute to AMD risk both independently and through their interactions with genes. Again, ongoing studies are teasing apart these contributions. However, risk is just one of the many facets of the overall genetic architecture of AMD. Disease progression and treatment response are two critical elements also influenced by genetic variation. The goal of this proposal is to increase our understanding of the genetic etiology of progression and treatment response in AMD, both of which have been understudied. Identifying the genes underlying clinical outcomes is directly relevant to better directing current treatments and developing new and better treatments and regimens for those suffering this disabling disorder.

Mapes Lab | Project Leader: Brian Mapes
Fund Title:  Understanding predictability and model error . . .
Fund Source:  Office of Naval Research (ONR)
CPU Hours: 1,000,000  | IDSC Focus Area: Earth Systems
Scientific Justification:  Our global atmosphere models need to be kept on track by nudging their state to observed state sequences through time. Those target state sequences are large 4D datasets that need to be consulted during runtime. At the same time, we need to output all the tendencies including the nudging tendency for diagnosis, so that too requires space.

Addiction Study | Project Leaders: Deborah Mash, IDSC Fellow Chun Wu
Fund Source:  Epigenetic Grant from the National Institute on Drug Abuse
CPU Hours: 50,000  | IDSC Focus Area:  Drug Discovery
Scientific Justification: Discovery science suggests that drug addiction and obesity are defined as disorders in which the saliency of food or drug reward becomes exaggerated and share some neurobiological overlaps. Several common neuropeptides and hormones regulate the excessive consumption of both addictive drugs and palatable food, such as insulin and leptin, which are involved in the mesolimbic and nigrostriatal dopamine (DA) system that regulate food and drug use. This study is focused on identifying common molecular targets for addiction and obesity for medication development.

The History of the first “Pegasus”

The word “supercomputer” was first coined in the 1960s by the Control Data Corporation as a marketing term for its CDC 6600, designed by Seymour Cray before he left to found his own supercomputing company.

The concept of supercomputing stretches back still further. British company Ferranti was one of the forerunners of affordable scientific computing, releasing its “Pegasus 1” system in 1956. The technology found in the Pegasus is, naturally, antiquated: considered fast at the time, its speed of a few thousand operations per second is outstripped by even the most modest modern smartphone.

Each generation of supercomputer typically at least doubles the performance of its predecessors, either through technological innovation – the replacement of vacuum tubes with solid-state transistors led to a massive increase in both performance and reliability, for example – or through brute force, adding in more components and cabinets.

Some things in the industry don’t change; a typical supercomputer today takes up a good portion of a room, as did the Ferranti Pegasus 1, and requires specialist staff, a robust power supply and adequate cooling.

(Source: PCpro “The World’s Most Powerful Supercomputers” | Site now by subscription only.)