Computational Science and HPC Lab
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
HPC Cluster for MPI and CUDA based Parallelization of Computationally expensive problems.
OPENMPI- open source implementation of MPI