Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
On reducing transitions through data modifications
DATE '99 Proceedings of the conference on Design, automation and test in Europe
Reducing bus transition activity by limited weight coding with codeword slimming
GLSVLSI '00 Proceedings of the 10th Great Lakes symposium on VLSI
Power-optimal encoding for a DRAM address bus
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Memory Bus Encoding for Low Power: A Tutorial
ISQED '01 Proceedings of the 2nd International Symposium on Quality Electronic Design
On-Chip Communication Architectures: System on Chip Interconnect
On-Chip Communication Architectures: System on Chip Interconnect
A new array architecture for signed multiplication using Gray encoded radix-2m operands
Integration, the VLSI Journal
Efficient evolutionary approaches for the data ordering problem with inversion
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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Recently, in [3], the following problem was addressed: Given a set of data words or messages to be transmitted over a bus such that the sequence (order) in which they are transmitted is irrelevant, determine the optimum sequence that minimizes the total number of transitions on the bus. In 1994, Stan and Burleson [5] presented the bus-invert method as a means of encoding words for reducing I/O power, in which a word may be inverted and then transmitted if doing so reduces the number of transitions. In this paper, we combine the two paradigms into one — that of sequencing words under the bus-invert scheme for the minimum transitions, i.e., words can be complemented, reordered and then transmitted. We prove that this problem DOPI — Data Ordering Problem with Inversion — is NP-complete. We present a polynomial-time approximation algorithm to solve DOPI that comes within a factor of 1.5 from the optimum. Experimental results show that, on average, the solutions generated by our algorithm were within 4.4% of the optimum, and that resequencing along with complementation leads to 34.4% reduction in switching activity.