Supporting the Research and the Researchers
Science and engineering increasingly rely on numerical analysis and computational simulations to better understand the underlying details of the complex phenomena. From the study of the cosmos to the design of unmanned vehicles and exploration of human genetics, today's research makes intensive use of computational resources.
ARC supports the efforts of our computational researchers by making available a broad spectrum of high-end robust hardware and up-to-date commercial software.
Linux Computer Clusters
WPI has several HPC Clusters the most powerful being the one most recently acquired through an NSF MRI grant. This cluster features 480 Intel Xeon E-5 2680v2 @2.8GHz CPUs and 48 Nvidia Tesla K40m GPUs each one with Peak double precision floating point performance of 1.43 Tflops. Equipped with 12 GB of memory, the Tesla K40 GPU accelerator is ideal for the most demanding HPC and big data problem sets.
Linux Compute Nodes
WPI offers many powerful state of the art Linux compute nodes to the faculty and students to run both commercial and open source applications.
Research Windows Terminal Servers
ARC maintains windows terminal servers which allow researchers to access powerful systems to run both commercial and open source code in a windows environment. The systems can be reached by remote desktop connection from all platforms (Windows, Linux, Mac).
Software & Code Development
WPI ARC team acquires, manages most of the academic software for WPI (Matlab, Maple, Ansys, Comsol, Solidworks, tecplot, Sigmaplot and a host of others) which then become accessible to the community through installation in the computer labs, Windows terminal servers and Linux servers and workstations.
Code Development: WPI ARC team offers Code development services. Knowledgeable staff in the areas of parallel computing with Fortran, C and Python. We help faculty and students write/debug/optimize their code on run on internal HPC clusters and if need be for other supercomputing centers. We offer short introductory training sessions as well as advanced ones for code development and parallelization.