Abstract:
Soft error is a significant reliability concern for nanometer technologies. Shrinking feature
sizes, lower voltage levels, reduced noise margins, and increased clock frequency improves
the performance and lowers the power consumption of integrated circuit. But it causes the
integrated circuit more susceptible to soft error that can corrupt data and make systems
Vulnerable. The =device shrinking ‘reduces the soft error tolerance of the VLSI circuits, as
very little energy is needed to change their states. In digital systems, where the reliability is
a great concern, the impact of soft errors may be very catastrophic. Safety critical systems
are very sensitive to soft errors. A bit flip due to soft error can change the value of critical
Variable. And consequently the system control flow can completely be changed which may
lead to system failure. To minimize the soft error risks, critical blocks are identified by
criticality analysis of the blocks and ranking among them. Highest ranked blocks are
considered as critical block. Refactoring is applied to minimize the criticality of the critical
blocks. Then a novel methodology is proposed to detect and recover from soft errors
considering only preceding variables and critical blocks rather than considering all
Variables and blocks in the whole program. The proposed method has less time overhead in
comparison to existing dominant approach.
Description:
This thesis is submitted to the Department of Computer Science and Engineering , Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, April 2012.
Cataloged from PDF Version of Thesis.
Includes bibliographical references (pages 57-62).