Cloudster: Cost-Effective Execution of HPC Applications on the Cloud
Cloud computing has increased greatly in popularity in recent years. The cloud has had significant success in the commercial arena. We are now starting to see similar success in the area of parallel scientific applications, given that cloud computation, communication, and I/O are rapidly improving. The cloud has several attractive features for high-performance computing (HPC) users, especially as the HPC clientele continues to broaden and it becomes more difficult to access the traditional HPC clusters at national laboratories and companies.
In this project we are investigating ways to lower the barrier to HPC application programmers using the cloud. In particular, this means utilizing all possible ways to achieve good performance at the lowest possible cost.
People
- Faculty:
- David Lowenthal
- Postdoc:
- Aniruddha Marathe
Publications
Aniruddha Marathe, Rachel Harris, David K. Lowenthal, Bronis de Supinski,
Barry Rountree, and Martin Schulz.
Aniruddha Marathe, Rachel Harris, David K. Lowenthal, Bronis de Supinski,
Barry Rountree, and Martin Schulz.
Exploiting Redundancy for Cost-Effective, Time-Constrained
Execution of HPC Applications on Amazon EC2.
23rd ACM Symposium on High-Performance Parallel Distributed
Computing (HPDC),
June 2014.
Paper: PDF
A Comparative Study of High-Performance Computing on the Cloud.
22nd ACM Symposium on High-Performance Parallel Distributed Computing (HPDC),
June 2013.
Paper: PDF
This material is based upon work supported by the National Science Foundation (NSF) under grant no. CNS-1216829. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of NSF.