The LTS Research Computing group (HPC) provides system administration for our central Linux clusters and other servers, support for open-source and research software development and performance optimization, and consulting and proposal assistance to the university research community.Tweets by @LehighHPC
Maia, a 32-core, 128GB RAM system (2 x AMD Opteron 6380, 2.5GHz), was placed in service on June 18, 2013. All Lehigh University students, faculty and staff may request an account for work on Maia. For details on using Maia, please consult new documentation (available on-campus or via VPN) at the Research Computing wiki. In particular, please review the article for Polaris on the wiki; this is the system to which SSH connections are made to submit jobs for Maia.
Both LEAF and Altair will be removed from service on July 1, 2013; these systems are functionally obsolete.
Maia, a 32-core, 128GB RAM system (2 x AMD Opteron 6380, 2.5GHz), will be placed in service on June 18, 2013, replacing the current “no-cost” LEAF and Altair systems. All Lehigh University students, faculty and staff may request an account on Maia. All computing tasks on Maia (including interactive shell sessions) will be managed via a scheduling server named Polaris. No use of graphical user interface (GUI) programs will be supported on Maia. Some GUI-based programs provide for command-line use; these components will be supported on Maia.
For full details, including details on migration to Maia and action items for current LEAF and Altair users, please see the announcement (PDF).
SiPE is targeted at an audience of not just computer scientists but especially scientists and engineers, including a mixture of undergraduates, graduate students, faculty and staff.
These workshops focus on fundamental issues of HPC as they relate to Computational and Data-enabled Science & Engineering, including:
- the storage hierarchy
- instruction-level parallelism
- high performance compilers
- shared memory parallelism (e.g., OpenMP)
- distributed parallelism (e.g., MPI)
- HPC application types and parallel paradigms
- multicore optimization
- high throughput computing
- GPGPU computing
- scientific and I/O libraries
- scientific visualization
The key philosophy of the SiPE workshops is that an HPC-based code should be maintainable, extensible and, most especially, portable across platforms, and should be sufficiently flexible that it can adapt to, and adopt, emerging HPC paradigms.
The past year at Lehigh University has seen great transformation and augmentation to the High Performance Computing Facilities. See more.
Last Modified: 20120307T1103