Multicore Performance Prediction – Comparing Three Recent Approaches in a Case Study
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-48340-1_22
Reference19 articles.
1. Ardalani, N., Lestourgeon, C., Sankaralingam, K., Zhu, X.: Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance. In: International Symposium on Microarchitecture. ACM (2015)
2. ARM: ARM Fast Models. https://developer.arm.com/tools-and-software/simulation-models/fast-models . Accessed 17 May 2019
3. Arndt, O.J., Becker, D., Banz, C., Blume, H.: Parallel implementation of real-time semi-global matching on embedded multi-core architectures. In: International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS). IEEE (2013)
4. Arndt, O.J., Lefherz, T., Blume, H.: Abstracting parallel programming and its analysis towards framework independent development. In: International Symposium on Embedded Multicore/Many-Core Systems-on-Chip (MCSoC). IEEE (2015)
5. Arndt, O.J., Linde, T., Blume, H.: Implementation and analysis of the histograms of oriented gradients algorithm on a heterogeneous multicore CPU/GPU architecture. In: Global Conference on Signal and Information Processing (GlobalSIP). IEEE (2015)
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