[Zurück]

S. Pudukotai Dinakarrao, H. Yu, H. Huang, D. Xu:
"A Q‐Learning based Self‐adaptive I/O Communication for 2.5D Integrated Many‐core Microprocessor and Memory";
IEEE Transactions on Computers, 65 (2016), 4; S. 1185 - 1196.

A self-adaptive output-voltage swing adjustment is introduced in the design of energy-efficient I/O communication for 2.5D integrated many-core microprocessor and memory. Instead of transmitting signal with large voltage swing, a Q-learning based I/O management is deployed to adaptively adjust the I/O output-voltage swing under constraints of both communication power and bit error rate (BER). Simulation results show that the proposed adaptive 2.5D I/Os (in 65 nm CMOS) can achieve an average of 12.5 mW I/O power, 4 GHz bandwidth and 3.125 pJ/bit energy efficiency for one channel under 10^{-6} BER. With the use of conventional Q-learning and further accelerated Q-learning, we can achieve 12.95 and 18.89 percent power reduction and 14 and 15.11 percent energy efficiency improvement when compared to the use of uniform output-voltage swing based I/O communication.

error statistics;multiprocessing systems;2.5D integrated many-core microprocessor;2.5D memory;BER;CMOS;I/O management;Q-learning;bit error rate;communication power;energy-efficient I/O communi

http://dx.doi.org/10.1109/TC.2015.2439255