Power Point Slides aus Rutgers - und anderswo
http://archive.dimacs.rutgers.edu/Workshops/Parallel/slides/…
wie gehts weiter in der nach - Moore - Ära?
einige Impulse, sehr subjektiv gesammelt
Computational Electromagnetics in Post-Moore’s Law Era: Verification, Validation, and Benchmarking
Adapting Mobile To A Post-Moore’s Law Era
IC 'megatrends' point to post-Moore's Law era, warns TSMC's Chang
predicted feature size in 2024 (7.5 nm) = ~32 silicon atoms (Si-Si lattice distance is 0.235 nm)
Rock’s Law: Cost of semiconductor chip fabrication plant doubles every four years
low entropy computations
CS is lacking a good algorithmic theory of entropy
Communication can be much cheaper if “known in advance”
Self-Organizing Computations
• Hardware continuously changes (failures, power management)
• Algorithms have more dynamic behavior (multigrid, multiscale – adapt to evolution of simulated system)
• Mapping of computation to HW needs to be continuously adjusted
• Too hard to do in a centralized manner -> Need distributed, hill climbing algorithms
Resiliency
• HW for fault correction (and possibly fault detection) may be too expensive (consumes too much power)
• and is source of jitter
• Current global checkpoint/restart algorithms cannot cope with MTBF of few hours or less
• Need SW (language, compiler, runtime) support for error compartmentalization
• Catch error before it propagates
• May need fault-tolerant algorithms
• Need new complexity theory
The Von Neumann Bottleneck
Quantum Computing
Neuromorphic Computing
Optical Computing
Bioinformatics
is It Time To Rethink The Scientific Method?
Bioinformatics
Big Data
machine learning algorithms
the Democratization of Exploratory Research
The End of Moore's Law: A New Beginning for Information Technology
