Communications of the ACM
Another view on parallel speedup
Proceedings of the 1990 ACM/IEEE conference on Supercomputing
Proceedings of the 32nd annual ACM/IEEE international symposium on Microarchitecture
Isoefficiency: Measuring the Scalability of Parallel Algorithms and Architectures
IEEE Parallel & Distributed Technology: Systems & Technology
Getting Gigascale Chips: Challenges and Opportunities in Continuing Moore's Law
Queue - Power Management
Single-ISA Heterogeneous Multi-Core Architectures for Multithreaded Workload Performance
Proceedings of the 31st annual international symposium on Computer architecture
Corollaries to Amdahl's Law for Energy
IEEE Computer Architecture Letters
Amdahl's Law in the Multicore Era
Computer
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
WiDGET: Wisconsin decoupled grid execution tiles
Proceedings of the 37th annual international symposium on Computer architecture
Forwardflow: a scalable core for power-constrained CMPs
Proceedings of the 37th annual international symposium on Computer architecture
Modeling critical sections in Amdahl's law and its implications for multicore design
Proceedings of the 37th annual international symposium on Computer architecture
IEEE Micro
A QHD-capable parallel H.264 decoder
Proceedings of the international conference on Supercomputing
Dark silicon and the end of multicore scaling
Proceedings of the 38th annual international symposium on Computer architecture
CMP off-chip bandwidth scheduling guided by instruction criticality
Proceedings of the 27th international ACM conference on International conference on supercomputing
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Several recent works predict the future of multicore systems or identify scalability bottlenecks based on Amdahl's law. Amdahl's law implicitly assumes, however, that the problem size stays constant, but in most cases more cores are used to solve larger and more complex problems. There is a related law known as Gustafson's law which assumes that runtime, not the problem size, is constant. In other words, it is assumed that the runtime on p cores is the same as the runtime on 1 core and that the parallel part of an application scales linearly with the number of cores. We apply Gustafson's law to symmetric, asymmetric, and dynamic multicores and show that this leads to fundamentally different results than when Amdahl's law is applied. We also generalize Amdahl's and Gustafson's law and study how this quantitatively effects the dimensioning of future multicore systems.