Category Archives: ARC News

P100 GPU Nodes added to NewRiver

ARC is happy to announce the addition of 39 new GPU nodes to the NewRiver cluster. Each of these nodes is equipped with two Intel Xeon E5-2680v4 (Broadwell) 2.4GHz GPU (28 cores/node in all), 512 GB memory, and two NVIDIA P100 GPUs. Each GPU is capable of up to 4.7 TeraFLOPS of double-precision performance, so including CPU and GPU these nodes add over 400 TFLOPS of peak double-precision throughput to ARC’s resources.
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HPC Day at Virginia Tech

HPC Day Agenda

We are looking forward to seeing you at our Annual  HPC Day event March 24 from 10am-5pm! 
The event includes: a keynote by James Ahrens from LANL, a machine learning workshop, and faculty and student presentations.

Keynote: “Supercharging the Scientific Process Via Data Science at Scale”

Dr. James Ahrens is a senior research scientist at the Los Alamos National Laboratory (LANL). He is the founder and design lead of ParaView, a widely adopted visualization and data analysis package for large-scale scientific simulation data ( ParaView has had an extremely positive impact on the large-scale data analytic capabilities available to simulation scientists around the world. Dr. Ahrens graduated in 1989 with a B.S. in computer science from the University of Massachusetts and in 1996 with a Ph.D. in computer science from the University of Washington. At LANL, he is part of a data science team of twenty staff, postdocs and students. He is also a national leader of programmatic initiatives important to the United States Department of Energy’s National Nuclear Security Administration and Office of Science. Dr. Ahrens is the Data Analysis and Visualization lead for the U.S. Exascale Computing Project and the general chair for this year’s IEEE Scientific Visualization conference to be held in Phoenix, AZ in early October.

ARC and VT Libraries Sponsor Big Data Science Workshop

Featuring sessions on big data workflows, data visualization, data publishing, and reproducible research practices, the 2017 Big Data Science Workshop will also incorporate a brainstorming/strategy session aimed at improving research workflows, a networking breakfast, and lightning talks.

ARC’s Nicholas Polys and Brian Marshall each presented. The event flyer is here:

Big Data Science Workshop

New ARC Cluster: Cascades

ARC is happy to announce the release of a new cluster, named Cascades, available at and Cascades is a 196-node system capable of tackling the full spectrum of computational workloads, from problems requiring hundreds of compute cores to data-intensive problems requiring large amount of memory and storage resources. Cascade contains three compute engines designed for distinct workloads:

  • General – Distributed, scalable workloads. With Intel’s latest-generation Broadwell processors, 2 16-core processors and 128 GB of memory on each node, this 190-node compute engine is suitable for traditional HPC jobs and large codes using MPI.
  • GPU – Data visualization and code acceleration! There are four nodes in this compute engine which have – two Nvidia K80 GPUs, 512 GB of memory, and one 2 TB NVMe PCIe flash card.
  • Very Large Memory – Graph analytics and very large datasets. With 3TB (3072 gigabytes) of memory, four 18-core processors and 6 1.8TB direct attached SAS hard drives, 400 GB SAS SSD drive, and one 2 TB NVMe PCIe flash card , each of these two servers will enable analysis of large highly-connected datasets, in-memory database applications, and speedier solution of other large problems.

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New ARC Cluster: DragonsTooth

ARC is happy to announce the release of a new cluster, named DragonsTooth, available at DragonsTooth is made up of 48 nodes, each equipped with:

  • 2 x Intel Xeon E5-2680v3 (Haswell) 2.5 GHz 12-core CPU (same CPU as NewRiver)
  • 256 GB 2133 MHz DDR4 memory for large-memory problems
  • 4 x 480 GB SSD Hard Drives for fast local I/O ($TMPDIR)
  • 806 GFlops/s theoretical double-precision peak

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ARC presents at XSEDE16!

Dr. Srijith Rajamohan presented an Introduction to Python Pandas for Data Analytics tutorial. Pandas is a high-level open-source library that provides data analysis tools for Python. The audience was also introduced to relevant packages such as Numpy for fast numeric computation and Matplotlib/Bokeh for visualization to supplement the data analysis process. The slides for this tutorial can be found here.

Visualization GRA and Doctoral Candidate Ayat Mohammed presented a visualization showcase titled ‘Insights into Alzheimer’s Disease: Molecular Dynamics (MD) Simulations of Peptide-Membrane Interactions’ at XSEDE16, Miami. Also from ARC, Alana Romanella chaired the session on Workforce Development and Diversity.

ARC Interdisciplinary collaboration for analysis of food marketing/branding

Dr. Srijith Rajamohan and Dr. Nicholas Polys in ARC and Assistant Professor, Vivica Kraak in the Department of Human Nutrition, Foods, and Exercise are collaborating on a research project to map the world of celebrity endorsement of food and beverage brands, products and groups in the United States. HNFE doctoral student, Mi Zhou, is part of the research team with ARC MS student, Faiz Abidi, to build, analyze and visually display in 2D and 3D a database of more than 550 unique celebrities used to market food, beverage and restaurant products to children, teens and adults. The ARC team had helped build an open-source analytics and visualization engine to help address these needs.

The results of this project will be used to inform the policies and actions of diverse stakeholders including industry, government and public health groups to use celebrity endorsement, along with other integrated marketing communications, to promote healthy nutrient-profile products and behaviors that support healthy food environments for American children, adolescents and their parents. Prof. Kraak and her work was recently featured on the VT news which can be found here: