Creating a Microbenchmark with wide coverage of Memory-boundedness
| dc.contributor.author | Côté, Niklas | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för data och informationsteknik | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Computer Science and Engineering | en |
| dc.contributor.examiner | Pericas, Miquel | |
| dc.contributor.supervisor | Goel, Bhavishya | |
| dc.date.accessioned | 2022-11-30T15:24:27Z | |
| dc.date.available | 2022-11-30T15:24:27Z | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2020 | |
| dc.description.abstract | Memory-boundedness of an application is defined as the degree to which the performance of the application depends on the size and performance of memory instead of the CPU. The degree of memory-boundedness of an application determines its speedup when the CPU frequency is increased: an application with no memoryboundedness will exhibit linear speedup with frequency increase while an application with 100% memory-boundedness will exhibit no speedup at all. Dynamic voltage and frequency scaling (DVFS) is a power saving technique which aims to save energy by dynamically reducing frequency during the memory-bound phase of the application. The DVFS decision making is based on prediction models which predict the appropriate voltage and frequency for the application phase. To increase the accuracy of prediction models, training data needs to be collected from applications which exhibit varying degrees of compute-bound and memory-bound behavior. A single microbenchmark which can simulate wide variations of memory-boundedness behaviour could reduce the time required to train the prediction models and improve prediction accuracy. This thesis analyzes different measurement methods for memory-boundedness and proposes a new formula based on L3 cache misses which is believed to be a more suited fit for the definition of memory-boundedness. The testing of formulas was done on a benchmark suite from NASA called NAS Parallel Benchmarks (NPB), where the consistency and values of the formulas were evaluated. The result of measurements with the new L3 cache miss formula was then used to create a microbenchmark which can produce large variations of memory-boundedness. | |
| dc.identifier.coursecode | DATX05 | |
| dc.identifier.uri | https://odr.chalmers.se/handle/20.500.12380/305861 | |
| dc.language.iso | eng | |
| dc.setspec.uppsok | Technology | |
| dc.subject | DVFS | |
| dc.subject | memory-boundedness, | |
| dc.subject | microbenchmark | |
| dc.subject | benchmark | |
| dc.subject | voltage | |
| dc.subject | frequency | |
| dc.subject | prediction models | |
| dc.subject | static voltage | |
| dc.subject | dynamic voltage | |
| dc.title | Creating a Microbenchmark with wide coverage of Memory-boundedness | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | High-performance computer systems (MPHPC), MSc |