This HOWTO will demonstrate how to lower ones' disk space usage. The following procedures can be applied to all of OSC's file systems.
We recommend users regularly check their data usage and clean out old data that is no longer needed.
Users who need assistance lowering their data usage can contact OSC Help.
Search our client documentation below, optionally filtered by one or more systems.
The LAMMPS 14May16 known issue wherein parallel lammps spawned too many threads has been fixed on all clusters. No user action is required; if a user had applied the OMP_NUM_THREADS workaround then it may be removed, but it will not cause probems if left in place. The corrected executables were made the defaults for module lammps/14may16 at these times:
Darshan is a lightweight "scalable HPC I/O characterization tool
The following versions of Darshan are available on OSC clusters:
Apache Spark is an open source cluster-computing framework originally developed in the AMPLab at University of California, Berkeley but was later donated to the Apache Software Foundation where it remains today. In contrast to Hadoop's disk-based analytics paradigm, Spark has multi-stage in-memory analytics. Spark can run programs up-to 100x faster than Hadoop’s MapReduce in memory or 10x faster on disk. Spark support applications written in python, java, scala and R
Our current GPFS file system is a distributed process with significant interactions between the clients. As the compute nodes being GPFS flle system clients, a certain amount of memory of each node needs to be reserved for these interactions. As a result, the maximum physical memory of each node allowed to be used by users' jobs is reduced, in order to keep the healthy performance of the file system. In addition, using swap memory is not allowed.
The table below summarizes the maximum physical memory allowed for each type of nodes on our systems:
Caffe is "
From their README:
From WARP3D's webpage:
WARP3D is under continuing development as a research code for the solution of large-scale, 3-Dsolid models subjected to static and dynamic loads. The capabilities of the code focus on fatigue & fracture analyses primarily in metals. WARP3D runs on laptops-to-supercomputers and can analyze models with several million nodes and elements.
The following versions of WARP3D are available on OSC clusters:
The following are technical specifications for Owens.
824 nodes
1,648 (2 sockets/node)
23,392 (28 cores/node)
28 cores/node (48 cores/node for Huge Mem Nodes)
~1,500GB in /tmp
Amber 16 has been installed on the OSC clusters; usage is via the module amber/16. For information on available executables and installation details see the software page for Amber or the output of the module help command, e.g.: module help amber/16. On August 15, 2016 Amber 16 will be made the default amber module.
