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- Discover available resources
- Access XSEDE services and resources
- Access Data
- Move Data
- Start a computation
- Terminate a computation
- Submit a job
- Parallelize existing serial code
- Compile a program from source on a remote machine
- Submit a batch job
- Process gigabytes of data and transfer it back to a personal machine for further analysis
- Extend an algorithm to handle new or larger datasets.
- Use profiling tools to identify bottlenecks
- Employ optimization techniques to improve runtime efficiency
- Use parallel visualization tools to analyze output
- Debug error messages from the compiler or linker
- Identify target system for a code
- Identify programming language for code development
- Identify optimized numerical libraries for use in an application code to avoid implementing a basic numerical algorithm from scratch
- Locate training resources to support a specific activity
- Use a hardware accelerator/coprocessor like: Nvidia or AMD gpu, Intel XeonPhi
- Find the software I need (modules?) or install the software required (system, or my $HOME) so that I can : ./configure; make
- Monitor job status
- Get historical job information
- Get an estimate of start time of a submitted job
- Get a third party application and number seeds available in any or a specific resource
- Get benchmark data for a given application across XSEDE resources