Extending Amdahl’s Law for Multicores with Turbo Boost

Rewriting sequential programs to make use of multiple cores requires considerable effort. For many years, Amdahl’s law has served as a guideline to assess the performance benefits of parallel programs over sequential ones, but recent advances in multicore design introduced variability in the performance of the cores and motivated the reexamination of the underlying model. This paper extends Amdahl’s law for multicore processors with built-in dynamic frequency scaling mechanisms such as Intel’s Turbo Boost. Using a model that captures performance dependencies between cores, we present tighter upper bounds for the speedup and reduction in energy consumption of a parallel program over a sequential one on a given multicore processor and validate them on Haswell and Sandy Bridge Intel CPUs. Previous studies have shown that from a processor design perspective, Turbo Boost mitigates the speedup limitations obtained under Amdahl’s law by providing higher performance for the same energy budget. However, our new model and evaluation show that from a software development perspective, Turbo Boost aggravates these limitations by making parallelization of sequential codes less profitable.

[1]  G. Amdhal,et al.  Validity of the single processor approach to achieving large scale computing capabilities , 1967, AFIPS '67 (Spring).

[2]  Bashayer M. Al-Babtain,et al.  A SURVEY ON AMDAHL'S LAW EXTENSION IN MULTICORE ARCHITECTURES , 2013 .

[3]  Rami G. Melhem,et al.  Corollaries to Amdahl's Law for Energy , 2008, IEEE Computer Architecture Letters.

[4]  Hsien-Hsin S. Lee,et al.  Extending Amdahl's Law for Energy-Efficient Computing in the Many-Core Era , 2008, Computer.

[5]  James Charles,et al.  Evaluation of the Intel® Core™ i7 Turbo Boost feature , 2009, 2009 IEEE International Symposium on Workload Characterization (IISWC).

[6]  Gene M. Amdahl,et al.  Computer Architecture and Amdahl's Law , 2007, Computer.

[7]  Mark D. Hill,et al.  Amdahl's Law in the Multicore Era , 2008 .

[8]  Sebastian M. Londono,et al.  Extending Amdahl's law for energy-efficiency , 2010, 2010 International Conference on Energy Aware Computing.

[9]  Rami G. Melhem,et al.  On the Interplay of Parallelization, Program Performance, and Energy Consumption , 2010, IEEE Transactions on Parallel and Distributed Systems.

[10]  John Paul Shen,et al.  Mitigating Amdahl's law through EPI throttling , 2005, 32nd International Symposium on Computer Architecture (ISCA'05).

[11]  Ümit Y. Ogras,et al.  Constrained Energy Optimizationin Heterogeneous Platforms UsingGeneralized Scaling Models , 2015, IEEE Computer Architecture Letters.