Moore's Law has underwritten a remarkable period of growth and stability for the computer industry. The doubling of transistor density at a predictable cadence has fueled not only five decades of increased processor performance, but also the rise of the general-purpose computing model. However, according to a pair of researchers at MIT and Aachen University, that's all coming to an end.
Neil Thompson Research Scientist at MIT's Computer Science and A.I. Lab and a Visiting Professor at Harvard, and Svenja Spanuth, a graduate student from RWTH Aachen University, contend what we have been covering here at The Next Platform all along; that the disintegration of Moore's Law, along with new applications like deep learning and cryptocurrency mining, are driving the industry away from general-purpose microprocessors and toward a model that favors specialized microprocessor. "The rise of general-purpose computer chips has been remarkable. So, too, could be their fall," they argue.
As they point out, general-purpose computing was not always the norm. In the early days of supercomputing, custom-built vector-based architectures from companies like Cray dominated the HPC industry. A version of this still exists today in the vector systems built by NEC. But thanks to the speed at which Moore's Law has improved the price-performance of transistors over the last few decades, the economic forces has greatly favored general-purpose processors.
That's mainly because the cost of developing and manufacturing a custom chip is between $30 and $80 million. So even for users demanding high performance microprocessors, the benefit of adopting a specialized architecture is quickly dissipated as the shrinking transistors in general-purpose chips erases any initial performance gains afforded by customized solutions. Meanwhile, the costs incurred by transistor shrinking can be amortized across millions of processors.
From The Next Platform
View Full Article
No entries found