Skip to content
/ codes Public
forked from codes-org/codes

The Co-Design of Exascale Storage Architectures (CODES) simulation framework builds upon the ROSS parallel discrete event simulation engine to provide high-performance simulation utilities and models for building scalable distributed systems simulations

License

Unknown, Unknown licenses found

Licenses found

Unknown
LICENSE
Unknown
LICENSE.md
Notifications You must be signed in to change notification settings

mmubarak/codes

 
 

Repository files navigation

CODES Discrete-event Simulation Framework

Join our CODES user mailing list to stay up to date with major changes, events, and news!

Discrete event driven simulation of HPC system architectures and subsystems has emerged as a productive and cost-effective means to evaluating potential HPC designs, along with capabilities for executing simulations of extreme scale systems. The goal of the CODES project is to use highly parallel simulation to explore the design of exascale storage/network architectures and distributed data-intensive science facilities.

Our simulations build upon the Rensselaer Optimistic Simulation System (ROSS), a discrete event simulation framework that allows simulations to be run in parallel, decreasing the simulation run time of massive simulations to hours. We are using ROSS to explore topics including large-scale storage systems, I/O workloads, HPC network fabrics, distributed science systems, and data-intensive computation environments.

The CODES project is a collaboration between the Mathematics and Computer Science department at Argonne National Laboratory and Rensselaer Polytechnic Institute. We collaborate with researchers at University of California at Davis to come up with novel methods for analysis and visualizations of large-scale event driven simulations. We also collaborate with Lawrence Livermore National Laboratory for modeling HPC interconnect systems.

About

The Co-Design of Exascale Storage Architectures (CODES) simulation framework builds upon the ROSS parallel discrete event simulation engine to provide high-performance simulation utilities and models for building scalable distributed systems simulations

Resources

License

Unknown, Unknown licenses found

Licenses found

Unknown
LICENSE
Unknown
LICENSE.md

Stars

Watchers

Forks

Packages

No packages published

Languages

  • C 91.0%
  • Python 4.8%
  • M4 2.8%
  • Lex 0.5%
  • C++ 0.3%
  • Shell 0.3%
  • Other 0.3%