Minimizing Energy and Computation in Long-Running Software
| Author | Gelenbe E.; Siavvas M. |
|---|---|
| Title | Minimizing Energy and Computation in Long-Running Software |
| Journal | Applied Sciences |
| Year | 2021 |
| Status | Published |
| Volume | 11 |
| Issue | 3 |
| DOI | 10.3390/app11031169 |
| Abstract | <p>Long-running software may operate on hardware platforms with limited energy resources<br /> such as batteries or photovoltaic, or on high-performance platforms that consume a large amount<br /> of energy. Since such systems may be subject to hardware failures, checkpointing is often used to<br /> assure the reliability of the application. Since checkpointing introduces additional computation time<br /> and energy consumption, we study how checkpoint intervals need to be selected so as to minimize a<br /> cost function that includes the execution time and the energy. Expressions for both the program’s<br /> energy consumption and execution time are derived as a function of the failure probability per<br /> instruction. A first principle based analysis yields the checkpoint interval that minimizes a linear<br /> combination of the average energy consumption and execution time of the program, in terms of the<br /> classical “Lambert function”. The sensitivity of the checkpoint to the importance attributed to energy<br /> consumption is also derived. The results are illustrated with numerical examples regarding programs<br /> of various lengths and showing the relation between the checkpoint interval that minimizes energy<br /> consumption and execution time, and the one that minimizes a weighted sum of the two. In addition,<br /> our results are applied to a popular software benchmark, and posted on a publicly accessible web<br /> site, together with the optimization software that we have developed.</p> |
| Minimizing Energy and Computation in Long-Running.pdf |