CODES 0.4.1 has been released! This is a hotfix release that fixes an incompatibility with recent ROSS revisions. The new version can be found at http://www.mcs.anl.gov/research/projects/codes/downloads/ .

The slides for (most of) the Summer of CODES 2015 talks have been made available. Check them out over at http://press3.mcs.anl.gov/summerofcodes2015/workshop-proceedings/.

Thanks to all that attended the Summer of CODES 2015 Workshop! We had a strong first showing and a full schedule of engaging talks. We will post slides onto the workshop website (http://press3.mcs.anl.gov/summerofcodes2015/) in the coming days.

CODES 0.4.0 has been released! You can find the release here.
Notable in this release include a large cleanup/refactoring of the codebase, improvements to error handling, numerous bugfixes, and improved documentation. Additionally, the workload generator API for IO and networking has been merged, though the overall implementation is still in experimental phase.
Full changelog (can also be found at doc/RELEASE_NOTES in the codes-base/codes-net tarballs):

codes-base

general:
==========
significant source reorganization / refactoring
refactor some private headers out of the public eye
dead code removal
documentation:
==========
improved example_heterogeneous example program
added configuration to example_heterogeneous showing two torus networks
reorganized files to prevent name collisions on OSX. Top-level docs other than
copyright now in doc directory
additions to best practice document
configurator:
==========
more stable file format for configurator output
ignore unrelated parameters passed into filter_configs
handle empty cfields in configurator
workloads:
==========
combined network and IO workload APIs into a single one
adding dumpi workload support in codes-workload-dump utility
workload dump utility option cleanup
renamed “bgp” workload generator to “iolang”, significant cleanups
put network workload ops in workload dump util
removing one of the dumpi libraries from the build. It was generating some unwanted dumpi files.
network workload API more fleshed out
utilities:
==========
configuration bug fixes for larger LP type counts
resource LP annotation mapping hooks
local storage model API switch to use annotations
better configuration error handling
hedge against precision loss in codes_local_latency (see codes.h)
use a different RNG than default for codes_local_latency
– prevents addition/removal of codes_local_latency calls from poisoning RNG
stream of calling model
added simple GVT-aware stack with garbage collection (see rc-stack.h)

codes-net

general:
==========
cleanup of much of the code base
more informative error for failure to find modelnet lps
removed redundant include directory on install (was ‘install/codes/codes/*.h’)
documentation:
==========
reorganized files to prevent name collisions on OSX. Top-level docs other than
copyright now in doc directory
updated code documentation
fix linker error in certain cases with codes-base
tweaked config error handling
networks:
==========
fix to loggp latency calculation when using “receive queue”
made torus lps agnostic to groups and aware of annotations
miscellaneous fixes to dragonfly model
updates to simplep2p: support for having different latency/bw at sender &
receiver end. See src/models/networks/model-net/doc/README.simplep2p.txt
minor fixes to usage of quickhash in replay tool
fixed RNG reverse computation bug in loggp
fixed swapped arguments in round-robin scheduler causing short circuit
workloads:
==========
minor changes to dumpi trace config files
resolving minor bug with reverse computation in dumpi traces
Updating network trace code to use the combined workload API
Adding synthetic traffic patterns (currently with dragonfly model)
Adding network workload test program for debugging
Updating MPI wait/wait_all code in replay tool

CODES 0.3.0 is released! This marks the first formal release of the codes-base and codes-net projects. You can find the release on the download page.
Against recent repository revisions, this release includes more complete and cleaned up documentation.

Chris Carothers presented “Combining Aspen with massively parallel simulation for effective exascale co-design” at the 2013 Workshop on Modeling & Simulation of Exascale Systems & Applications on September 18, 2013. It proposes leveraging a formal performance modeling language in conjunction with parallel discrete event simulation for multiresolution performance prediction and evaluation.

Lawrence Livermore National Laboratory has announced that the ROSS simulation toolkit achieved a record-breaking simulation speed of 504 billion events per second on LLNL’s Sequoia Blue Gene/Q supercomputer. The work will be presented in “Warp Speed: Executing Time Warp on 1,966,080 Cores,” at the ACM SIGSIM PADS 2013 conference.

Misbah Mubarak presented “Modeling a million-node dragonfly network using massively parallel discrete-event simulation” at the 2012 Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems (PMBS12).  It demonstrates how a dragonfly network with up to 50 million nodes can be simulated with high fidelity using CODES.

The goal of the CODES project is use highly parallel simulation to explore the design of exascale storage architectures and distributed data-intensive science facilities.

Increasingly, science endeavors rely heavily on data management, analysis, and storage as part of the discovery process. To serve large communities of scientists, complex systems and instruments are deployed across multiple institutions to manage and analyze data produced from experiments, observational platforms, and computational simulation. Evaluating designs and coordinating deployment and operation of such a virtual data facility poses a significant challenge. An ability to simulate these environments would transform the approach taken to design, procurement, tuning, and upgrade of these 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 also collaborate with Lawrence Livermore National Laboratory for modeling HPC interconnect systems.