Static power analysis for power-driven synthesis
Author(s) -
ShihYi Yuan,
KeHorng Chen,
J.–Y. Jou,
SyYen Kuo
Publication year - 1998
Publication title -
iee proceedings - computers and digital techniques
Language(s) - English
Resource type - Journals
eISSN - 1359-7027
pISSN - 1350-2387
DOI - 10.1049/ip-cdt:19981909
Subject(s) - benchmark (surveying) , computer science , node (physics) , spice , power analysis , power optimization , probabilistic logic , power (physics) , set (abstract data type) , electronic circuit , cmos , algorithm , electronic engineering , computer engineering , power consumption , engineering , electrical engineering , artificial intelligence , physics , structural engineering , geodesy , quantum mechanics , cryptography , programming language , geography
A new static power analysis method for CMOS combinational circuits is presented. This approach integrates the simulation-based method and the probabilistic method. And can establish the relationships between the primary inputs and the internal nodes in the circuit. Based on the relationships, our approach can also indicate which internal node or input sequence consumes the most power. It is thus suitable for performing power estimation in the synthesis environment for power optimisation. To the best of our knowledge, this is the first attempt to develop a systematic way to symbolically represent the relationships between the primary inputs and the power consumption at every internal node of a circuit. Furthermore, by using the existing piecewise linear delay model, as well as the proposed algorithm, this novel method is also very accurate and efficient. For a set of benchmark circuits, the experimental results show that the power estimated by our technique is within 5% error as compared with that by the exact SPICE simulation, while the execution speed is more than four orders of magnitude faster
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom