Efficient testing of SRAM with optimized March sequences and a novel DFT technique for emerging failures due to process variations

Authors:
Qikai Chen;Hamid Mahmoodi;Swarup Bhunia;Kaushik Roy
Affiliations:
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Engineering, San Francisco State University, San Francisco, CA and School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN;School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN
Venue:
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Year:
2005

Citing 11
Cited 2

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Abstract

With increasing inter-die and intra-die parameter variations in sub-100-nm process technologies, new failure mechanisms are emerging in CMOS circuits. These failures lead to reduction in reliability of circuits, especially the area-constrained SRAM cells. In this paper, we have analyzed the emerging failure mechanisms in SRAM caches due to transistor Vt variations, which results from process variations. Also we have proposed solutions to detect those failures efficiently. In particular, in this work, SRAM failure mechanisms under transistor Vt variations are mapped to logic fault models. March test sequences have been optimized to address the emerging failure mechanisms with minimal overhead on test time. Moreover, we have proposed a design for test circuit to complement the March test sequence for at-speed testing of SRAMs. The proposed technique, referred as double sensing, can be used to test the stability of SRAM cells during read operations. Using the proposed March test sequence along with the double sensing technique, a test time reduction of 29% is achieved, compared to the existing test techniques with the same fault coverage. We have also demonstrated that double sensing can be used during SRAM normal operation for online detection and correction of any number of random read faults.