ARC materials which highlight the cyberinfrastructure and services available from ARC. See: DoIT_Welcome_ARC
Advanced Research Computing is pleased to announce the public release of its newest high-performance computing (HPC) system, NewRiver, to the academic and research community at Virginia Tech. The 134-node system has an aggregate peak computing capacity of 152 TFLOPs (trillions of floating point operations per second) and 33 terabytes (TB) of aggregate memory. In addition, NewRiver is one of the first computational clusters to use the latest generation of InfiniBand interconnect, EDR, which connects the compute and storages nodes at a peak speed of 100 Gigabits/second.
NewRiver is 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. NewRiver contains five compute engines designed for distinct workloads.
- General – Distributed, scalable workloads. With two of Intel’s latest-generation Haswell processors, 24 cores, and 128 GB memory on each node, this 100-node compute engine is suitable for traditional HPC jobs and large codes using MPI.
- Big Data – High performance data analytics. With 43.2 TB of direct-attached storage for each node, this system enables processing and analysis of massive datasets. The 16 nodes in this compute engine also have 512 gigabytes (GB) of memory, making them suitable for jobs requiring large memory.
- GPU – Data visualization and code acceleration. Nvidia K80 GPUs in this system can be used for code acceleration. They will also provide remote rendering, allowing large datasets to be viewed in place without lengthy data transfers to desktop PCs. The 8 nodes in this compute engine also have 512 GB of memory, making them suitable for jobs requiring large memory.
- Interactive – Rapid code development and interactive usage. Each of the eight nodes in this compute engine have 256 GB memory and a K1200 graphics card. A browser-based, client-server architecture allows for a responsive, desktop-like experience when interacting with graphics-intensive programs.
- Very Large Memory – Graph analytics and very large datasets. With 3TB (3072 gigabytes) of memory, four 15-core processors and 6 direct attached hard drives, each of the two servers in this system will enable analysis of large highly-connected datasets, in-memory database applications, and speedier solution of other large problems.
ARC’s computational scientists and support staff are available to help faculty and students choose the right compute engine for their research. ARC offers assistance with code development and optimization for high performance computing systems and installation of software.
Access to ARC’s resources is available to all Virginia Tech faculty, staff, and students. Higher priority access can be purchased through the Investment Computing Program, which provides a way for departments and individual faculty members to gain access to a larger share of resources than it is otherwise possible for ARC to provide. ARC’s BlueRidge cluster was partially funded by the investment program.
This tutorial, given by Srijith Rajamohan, and Peter Radics, covers the Python programming language including all the information needed to participate in the XSEDE15 Modeling Day event on Tuesday, July 27th, 2015. Topics covered are variables, input/output, control structures, math libraries, and plotting libraries. This tutorial uses Anaconda Python Package, that you can download here .
Click here to access the tutorial slides.
To check out pictures from the event, visit our Facebook Page.
ARC’s partnership with Wireless@VT has recently yielded a new NSF grant for visualizing radio spectrum! Clickhere to read the article.
ARC’s collaborations with Computer Science faculty are highlighted in a recent, Microsoft commercial that is airing nation-wide: The VT article with links to the YouTube videos is here, showing Dr. Feng and hist students exploring MPIBlast results with the immersive, embodied and high-resolution displays of the Visionarium Lab.