Research Output per year
Fingerprint Fingerprint is based on mining the text of the expert's scholarly documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 5 Similar Profiles
Supercomputers
Engineering & Materials Science
Water
Engineering & Materials Science
Best Practice
Mathematics
Monitoring
Engineering & Materials Science
Prefetching
Mathematics
Lattice QCD
Mathematics
Performance Modeling
Mathematics
Parallel architectures
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2006 2019
Best practices and lessons from deploying and operating a sustained-petascale system: The blue waters experience
Bauer, G. H., Bode, B., Enos, J. J., Kramer, W. T., Lathrop, S., Mendes, C. L. & Sisneros, R. R., Mar 11 2019, Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018. Institute of Electrical and Electronics Engineers Inc., p. 673-684 12 p. 8665815. (Proceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Best Practice
Water
Education
Leadership
Computing
Best practices for management and operation of large HPC installations
Lathrop, S., Mendes, C., Enos, J., Bode, B., Bauer, G., Sisneros, R. & Kramer, W., Aug 25 2019, In : Concurrency Computation. 31, 16, e5069.Research output: Contribution to journal › Article
Best Practice
Leadership
Supercomputers
Water
Resources
Roofline analysis with Cray performance analysis tools (CrayPat) and roofline-based performance projections for a future architecture
Kwack, J. H., Arnold, G., Mendes, C. & Bauer, G. H., Aug 25 2019, In : Concurrency Computation. 31, 16, e4963.Research output: Contribution to journal › Article
Performance Analysis
Projection
Compiler
Linear algebra
Performance Model
HPCG and HPGMG benchmark tests on multiple program, multiple data (MPMD) mode on Blue Waters—A Cray XE6/XK7 hybrid system
Kwack, J. H. & Bauer, G. H., Jan 10 2018, In : Concurrency Computation. 30, 1, e4298.Research output: Contribution to journal › Article
Conjugate Gradient
Hybrid systems
Hybrid Systems
Program processors
High Performance
Challenges of workload analysis on large HPC systems; A case study on NCSA Bluewaters
White, J. P., Innus, M., Jones, M. D., DeLeon, R. L., Simakov, N., Palmer, J. T., Gallo, S. M., Furlani, T. R., Showerman, M., Brunner, R. J., Kot, A., Bauer, G. H., Bode, B., Enos, J. J. & Kramer, W. T., Jul 9 2017, PEARC 2017 - Practice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact. Association for Computing Machinery, a6. (ACM International Conference Proceeding Series; vol. Part F128771).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Water
Supercomputers
Datasets
Monet - Blue Waters Network Dataset
Saurabh, J. (Creator), Archit, P. (Creator), Showerman, M. T. (Creator), Enos, J. J. (Creator), Bauer, G. H. (Creator), Kalbarczyk, Z. T. (Creator), Iyer, R. K. (Creator), Kramer, W. T. (Creator), University of Illinois at Urbana-Champaign, Oct 5 2019
DOI: 10.13012/B2IDB-2921318_V1
Dataset