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Computational Facilities

Computational Science and HPC Lab

30 Desktops with intel i5 quad core processors, 8GB RAM, NVIDIA graphics card.

Operating system : Scientific Linux
Compilers and Libraries: The entire GNU compiler suite – gcc, g++, and g77
The Java Execution and Development Environments.
Python programming language. Also Matplotlib, Numpy and Scipy
Parallel Programming Libraries and tools:
OpenMP – API for directing multi-threaded shared memory parallelism.
CUDA toolkit 6.5.
GNU Gprof – performance analysis tool for Unix applications.
Important Scientific Software: Scilab; Octave; R – software environment for statistical computing and graphics.
Visualization: Gnuplot. Paraview.
Documentation and reader: Latex

cs207

 

 

High Performance Computing  Cluster (GICS Cluster)

Master Node: 1

Number of Compute Nodes: 2 (16 Core, 32 GB RAM)
Number of CPU + GPU Nodes: 2 (16 core, 128 GB RAM, NVIDIA GTX 750)
Number of CPU Cores: 76

HDD: 25TB

OPENMPI- open source implementation of MPI

OS Installed: Scientific Linux 7.0
Cuda Toolkit : Cuda 7
Cluster Tool: Torque, OpenMP
Cluster Management: Ganglia
Installed Application: Paraview, VTK, PARADISO
cluster

GPU EDUCATION Center and GPU Research Center Supported by NVIDIA Corporation.

Number of GPU Servers : 4 (Tesla K40, GTX 680, GTX 680, GTX 690, GTX 750)

GPU-servers-web