PROJECT TITLE :

Scalable Approach for Power Droop Reduction During Scan-Based Logic BIST - 2017

ABSTRACT:

The generation of important power droop (PD) throughout at-speed take a look at performed by Logic Designed-In Self Take a look at (LBIST) is a serious concern for trendy ICs. In truth, the PD originated throughout check might delay signal transitions of the circuit underneath check (CUT): an impact that will be erroneously recognized as delay faults, with consequent erroneous generation of take a look at fails and increase in yield loss. In this paper, we propose a unique scalable approach to reduce the PD throughout at-speed check of sequential circuits with scan-based mostly LBIST using the launch-on-capture scheme. This is achieved by reducing the activity issue of the CUT, by proper modification of the take a look at vectors generated by the LBIST of sequential ICs. Our scalable solution permits us to scale back PD to a value almost like that occurring during the CUT in field operation, while not increasing the quantity of take a look at vectors required to attain a target fault coverage (FC). We have a tendency to gift a hardware implementation of our approach that needs limited area overhead. Finally, we show that, compared with recent alternative solutions providing a similar PD reduction, our approach permits a important reduction of the number of test vectors (by more than fifty%), thus the take a look at time, to attain a target FC.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here


PROJECT TITLE : Measuring Fitness and Precision of Automatically Discovered Process Models: A Principled and Scalable Approach ABSTRACT: We are able to generate a process model by using automated process discovery techniques,
PROJECT TITLE : Scalable and Practical Natural Gradient for Large-Scale Deep Learning ABSTRACT: Because of the increase in the effective mini-batch size, the generalization performance of the models produced by large-scale distributed
PROJECT TITLE : On Model Selection for Scalable Time Series Forecasting in Transport Networks ABSTRACT: When it comes to short-term traffic predictions, up to the scale of one hour, the transport literature is quite extensive;
PROJECT TITLE : PPD: A Scalable and Efficient Parallel Primal-Dual Coordinate Descent Algorithm ABSTRACT: One of the most common approaches to optimization is called Dual Coordinate Descent, or DCD for short. Due to the sequential
PROJECT TITLE : On-Device Scalable Image-Based Localization via Prioritized Cascade Search and Fast One-Many RANSAC ABSTRACT: We describe a complete on-device solution for large-scale image-based urban localisation. Compact image

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry