Abstract
This work analyses the effects of sequential-to-parallel synchronization and inter-core communication on multicore performance, speedup and scaling from Amdahl's law perspective. Analytical modeling supported by simulation leads to a modification of Amdahl's law, reflecting lower than originally predicted speedup, due to these effects. In applications with high degree of data sharing, leading to intense inter-core connectivity requirements, the workload should be executed on a smaller number of larger cores. Applications requiring intense sequential-to-parallel synchronization, even highly parallelizable ones, may better be executed by the sequential core. To improve the scalability and performance speedup of a multicore, it is as important to address the synchronization and connectivity intensities of parallel algorithms as their parallelization factor.
| Original language | English |
|---|---|
| Pages (from-to) | 1-16 |
| Number of pages | 16 |
| Journal | Parallel Computing |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2014 |
| Externally published | Yes |
Bibliographical note
Funding Information:This research was partially funded by the Intel Collaborative Research Institute for Computational Intelligence and by Hasso-Plattner-Institut.
Funding
This research was partially funded by the Intel Collaborative Research Institute for Computational Intelligence and by Hasso-Plattner-Institut.
| Funders |
|---|
| Hasso-Plattner-Institut |
| Intel Collaboration Research Institute for Computational Intelligence |
Keywords
- Amdahl's law
- Analytical Performance Models
- Multicore
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