Sustainable Research Pathways for High-Performance Computing (SRP-HPC) is designed to help faculty and students at US academic institutions expand their research prowess and explore exciting career paths at Department of Energy (DOE) National Laboratories. SRP-HPC is a partnership with the DOE Exascale Computing Project (ECP), an aggressive multi-lab research, development, and deployment project focused on delivery of mission-critical applications, an integrated software stack, and exascale hardware technology advances.
We strongly encourage applicants from underrepresented backgrounds such as Black or African American, Hispanic/Latinx, American Indian, Alaska Native, Native Hawaiian, Pacific Islanders, women, persons with disabilities, first generation scholars, and students from smaller colleges and universities.
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Are you curious? Interested in seeing where your scientific interests can take you? Looking to find new collaborators and fascinating projects?
Wondering if SRP-HPC is right for you? Ask yourself these questions:
Do you want to learn more about the exciting and unprecedented opportunities available through exascale computing? The exponential increase in memory, storage, and compute power made possible by exascale systems is driving breakthroughs in computational and data-enabled science, analytics, learning, and artificial intelligence (AI) ─ which impact virtually all aspects of our world. There are countless opportunities (across mathematics, computer science, diverse scientific and engineering disciplines, data science and AI) to engage in cutting-edge research and development that provide the foundation for fulfilling careers and broad impact on society.
Ever imagined making discoveries that unlock the mysteries of science? Areas of work include developing simulation capabilities for chemistry, materials, energy, Earth and space science, data analytics, optimization, AI, national security, and more. Examples include:
- Revealing the underlying properties of matter
- Designing new materials and energy technologies
- Discovering the origin of the universe and chemical elements
- Validating the fundamental laws of nature
- Creating new techniques for data analytics and machine learning
Have you dreamed of applying your math or computer science skills to create cutting-edge software technologies that power HPC discoveries? Areas of work include open-source programming models and runtimes, scalable math libraries, data and visualization packages, development tools, and more. Examples include:
- Designing new computing and communication protocols for heterogeneous computer architectures
- Building tools that provide insight into code performance and memory usage
- Developing scalable libraries for sparse linear and nonlinear solvers, timestepping, and numerical optimization – exploring new algorithms for GPU-based architectures
- Developing capabilities for compressing, analyzing, moving, managing, and visualizing extreme-scale data
- Creating tools to build, test and integrate an emerging extreme-scale scientific software stack
Do you want to harness emerging exascale computer architectures to solve real world problems and develop the technology of the future? Work focuses on integrating key technologies on unprecedented computing hardware, including
- Advancing software integration and testing across emerging exascale environments
- Deploying an exascale software stack across DOE computing facilities, including
- Argonne Leadership Computing Facility (ALCF)
- National Energy Research Scientific Computing Center (NERSC)
- Oak Ridge Leadership Computing Facility (OLCF)
- Exploring facility resource utilization to ensure effective access to production systems
- Working on projects related to designing next-generation HPC systems
- Improving developer productivity and software sustainability as a key aspect of advancing scientific productivity
If you find any of these questions intriguing, have other related ideas, or you have any of the skills listed below, then you should apply for SRP-HPC!
Apply to SRP-HPC today!
Learn more: https://shinstitute.org/srp-hpc
Relevant skills, backgrounds or interests.
| Accelerators | Graph algorithms | Parallel features of modern Fortran |
| AI for computational science | Hardware architecture | Parallel simulations |
| Applied mathematics | Hardware evaluation | Parallel algorithm design |
| Astronomy | High-performance computing | Performance modeling & analysis |
| Atmospheric science | Hyperparameter optimization | Physics |
| C++ programming | Image processing | Programming |
| Calculus | Indexing techniques | Programming models |
| Chemistry | Information theory | Python |
| Climate science | Input/Output | Pytorch and HPC |
| Computational chemistry | Leadership computing | Randomized algorithms |
| Computational science | Low-level systems software | Research software engineering |
| Computer architectures | Machine learning | Runtimes |
| Computer engineering | Materials codes | Scientific computing |
| Computer science | Materials science | Scientific data analysis |
| Computing facilities | Math libraries | Security and performance |
| CUDA | Memory systems | Software deployment |
| Data analysis | MPI programming | Software development |
| Data management | Multiphysics modeling | Software engineering |
| Deep learning | Networking | Software sustainability |
| Development tools | Numerical linear algebra | Statistical mechanics |
| Device modeling | OpenACC | Statistical models |
| Dimensionality reduction | OpenMP | Statistics |
| Distributed computing | Open science | TCP protocols |
| Electrical engineering | Open-source software | Time-series analysis |
| Fluid dynamics | Operating system kernels | Turbulent flow |
| Glaciology | Optics | UNIX tools and computer systems |
| GPUs | Optimization | Visualization |
The deadline to apply is Friday, December 31, 2021.