The Center For Advanced Computing

The Center for Advanced Computing (CAC) delivers high performance computing, grid infrastructure, very large data storage, and advanced visualization services through the College of Engineering and throughout the University of Michigan.

With over 1000 processors, two high-speed switches for fast networking and terabytes of storage, the CAC can provide resources for most any computation problem you may have. If your problem is bigger than what we can handle, we can probably help you find resources more fitting for your problem size.

Please explore this site, starting with the Getting Started section to see how to get an account and start using the resources we have.

Lastly, if you have questions or concerns, please email us at cac-support@umich.edu.

Click here to apply for an account.

News

News: CAC Training - MPI The Library
Due to high demand, a second course is offered: The CAC is offering training for Message Passing (MPI) parallel programming. Training will take place on May 13th from 10am-12pm in 3358 AC Duderstadt.

Please register: MPI Spring 08
News: CAC Training - An Introduction to the CAC
Due to high demand, a second course is offered: The CAC is offering training for both the new and seasoned users. Training will take place on May 12th from 10am-12pm in 3358 AC Duderstadt.

Please register: Introduction Spring 08

Topics will include using PBS, compiling code, running applications, and available resources.
News: Lammps Updated to 1Apr08
Lammps on Nyx and Aon has been updated to version 1Apr08 (patch-set).
The New version has working kspace-PPM (Particle Particle Mesh), aspherical particles and force fields, and dissipative particle dynamics (DPD) force fields. There was also many bug fixes from the previous Lammps.

To use it run:
module load lammps/1Apr08 mpirun -np 4 lmp_linux < in.input
News: MSC Marc Available on Bighouse
Marc 2007r1 is available on bighouse. To use it run:

module load marc

Marc is also available on the CAC cluster nyx.



About the CAC Academics Getting Started Getting Help FAQ Resources Search The CAC Current Outages No outages have been reported Planned Outages No outages have been scheduled	The Center for Advanced Computing (CAC) delivers high performance computing, grid infrastructure, very large data storage, and advanced visualization services through the College of Engineering and throughout the University of Michigan. With over 1000 processors, two high-speed switches for fast networking and terabytes of storage, the CAC can provide resources for most any computation problem you may have. If your problem is bigger than what we can handle, we can probably help you find resources more fitting for your problem size. Please explore this site, starting with the Getting Started section to see how to get an account and start using the resources we have. Lastly, if you have questions or concerns, please email us at cac-support@umich.edu. Click here to apply for an account. News News: CAC Training - MPI The Library Due to high demand, a second course is offered: The CAC is offering training for Message Passing (MPI) parallel programming. Training will take place on May 13th from 10am-12pm in 3358 AC Duderstadt. Please register: MPI Spring 08 News: CAC Training - An Introduction to the CAC Due to high demand, a second course is offered: The CAC is offering training for both the new and seasoned users. Training will take place on May 12th from 10am-12pm in 3358 AC Duderstadt. Please register: Introduction Spring 08 Topics will include using PBS, compiling code, running applications, and available resources. News: Lammps Updated to 1Apr08 Lammps on Nyx and Aon has been updated to version 1Apr08 (patch-set). The New version has working kspace-PPM (Particle Particle Mesh), aspherical particles and force fields, and dissipative particle dynamics (DPD) force fields. There was also many bug fixes from the previous Lammps. To use it run: `module load lammps/1Apr08 mpirun -np 4 lmp_linux < in.input` News: MSC Marc Available on Bighouse Marc 2007r1 is available on `bighouse`. To use it run: `module load marc` Marc is also available on the CAC cluster `nyx`.