Computing node-hours on a CPU/GPU hybrid partition (Cray XC50) of the Piz Daint supercomputer. This service includes access to the high-performance Lustre scratch file system.
Computing node-hours on the multicore partition (Cray XC40) of the Piz Daint supercomputer. This service includes access to the high-performance Lustre scratch file system.
Compute node hours on the manycore nodes (Cray XC40 with KNL) of the Grand Tavè supercomputer.
OpenStack installation at CSCS offering classical Infrastructure-as-a-Service interfaces.
Every user is assigned their own home directory with sufficient storage space to store codes and documents (/home)
A shared parallel file system to store project data (/store or /project)
Space for storing specific datasets and perform backups on our tape library
Access to compute nodes is provided with the use of an integrated workload manager (Slurm). This provides traditional batch processing services through a pre-defined queue structure
The user can pack the Operating System (Linux), libraries and applications that are needed on on a Docker container, and then launch it inside a job using Shifter.
GREASY is a meta-scheduler to simplify the execution of embarrassingly parallel simulations in any environment.
This service enables users to define, create and manage their own infrastructure via a REST-ful API (IaaS). Users are then enabled to create their own services on top of it like web services or databases, among others.
Bidirectional data transfer services between /scratch and /store and between /store and any external location
Spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server, in order to access compute and storage resources interactively.
Jenkins is a continuous integration tool for scheduling code compilation
Amber (Assisted Model Building with Energy Refinement) is a collective name for a suite of programs that allow users to carry out molecular dynamics simulations, particularly on biomolecules
CP2K is a program to perform atomistic and molecular simulations of solid state, liquid, molecular and biological systems
The CPMD code is a plane wave/pseudopotential implementation of Density Functional Theory, particularly designed for ab initio molecular dynamics. Please note that a license has to be acquired from CPMD separately
GROMACS is a versatile package for performing molecular dynamics, i.e. to simulate the Newtonian equations of motion for systems with hundreds to millions of particles
LAMMPS is a classical molecular dynamics code that models an ensemble of particles in a liquid, solid, or gaseous state
NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems
Python is an interpreted high-level programming language for general-purpose programming
Quantum ESPRESSO is an integrated suite of open-source computer codes for nanoscale electronic structure calculations and materials modelling
The Vienna Ab initio Simulation Package (VASP) is a code for atomic scale materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics, from first principles. Please note that a license has to be acquired from VASP separately
Typical libraries for HPC applications such as HDF5, Trilinos, FFTW, BLAS or NetCDF. These are found in our systems but specific help on how to use them is not provided by CSCS.
Apache Spark is a fast general engine for large-scale data processing
TensorFlow is an open-source software library for numerical computation using data flow
Theano is a Python library that allows efficient definition, optimisation and evaluation of mathematical expressions involving multi-dimensional arrays
CGE is a highly optimized and scalable graph analytics application software, designed for high-speed processing of interconnected data
Anaconda is a distribution of the Python and R programming languages for large-scale data processing, predictive analytics, and scientific computing. It aims at simplifying package management and deployment.
BigDL is a distributed deep learning library for Spark that can run directly on top of existing Spark or Apache Hadoop clusters. Deep learning applications can be written as Scala or Python programs
Dask is a parallel programming library that combines with the Numeric Python ecosystem to provide parallel arrays, data-frames, machine learning, and custom algorithms
ABCpy is a highly modular, scientific library for Approximate Bayesian Computation (ABC) written in Python.
The Cray Compiling Environment (CCE) is a release of the Cray Fortran and Cray C compilers for use on x86-based Cray systems
Intel compilers produce optimised code that can run significantly faster by taking advantage of the ever-increasing core count and vector register width of Intel processors
The GNU Compiler Collection (GCC) includes the GNU Fortran compiler (gfortran), C (gcc) and C++ (g++) compilers
The PGI compiler suite includes Fortran 77, Fortran 90/95, C and C++ compilers.
The NVIDIA CUDA Toolkit provides a development environment for creating high performance GPU-accelerated applications
DDT provides source-level debugging of Fortran, C and C++ codes
CrayPat is a performance analysis tool developed by Cray for CSCS production systems
The mission of the Virtual Institute - High Productivity Supercomputing (VI-HPS) is to improve the quality and accelerate the development process of complex simulation codes in science and engineering that are being designed to run on highly-parallel computer systems
NVIDIA profiling tools and APIs for understanding and optimising the performance of CUDA and OpenACC applications
EasyBuild is a software installation framework in Python that allows you to install software in a structured and robust way
ParaView is an open-source, multi-platform data analysis and visualisation application
VisIt is an open-source, interactive, scalable, visualisation, animation and analysis tool
VMD is a molecular visualisation program for displaying, animating, and analysing large biomolecular systems using 3-D graphics and built-in scripting
All questions and service requests should be submitted through support.cscs.ch. An FAQ section is also available.
Every year there are several tutorials and courses for CSCS users