Lecture
Design for Testability: Techniques and Methods
In course
DEMO: nulla ipsum
Excepteur culpa incididunt tempor qui reprehenderit consectetur do ut dolore dolore enim anim eu. Aliquip id velit ad qui. Et enim sint excepteur veniam aute. Ea consequat cupidatat consequat minim mollit aute sunt magna esse. Aliquip enim minim eu anim magna. Cupidatat quis duis aliquip anim id nisi ex officia excepteur eu.
Description
This lecture covers the importance of Design for Testability (DFT) in VLSI systems, focusing on techniques to detect faults, reduce testing complexity, and improve test access. It discusses ad-hoc DFT methods, structured DFT approaches, scan design, scan operating modes, and scan layout procedures. The presentation also includes insights on multiple scan and partial scan techniques, as well as the evolution of testing methods from traditional bed of nails to modern JTAG standards.
Instructor
non dolore
Ut fugiat nostrud cillum ullamco non. Ex tempor velit pariatur enim aliquip sit. Aliquip laboris in pariatur magna id mollit labore laborum veniam anim est proident nisi nulla. Officia amet anim ullamco velit enim amet. Nulla consectetur ipsum sit adipisicing duis laborum ea. Duis incididunt nostrud culpa ullamco ut enim duis minim pariatur. Deserunt irure velit commodo duis laboris non commodo.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related lectures (32)
Design for Testability: Techniques and Hardware
Explores DFT techniques, scan design, JTAG boundary scan, and system test logic.
The fast Fourier transformMOOC: Digital Signal Processing I
Explores the history and efficiency of the fast Fourier transform algorithm, demonstrating its practical applications and computational advantages.
Discrete Fourier Transform: Introduction and Sampling
Covers the introduction of discrete Fourier transform and its implications on signal reconstruction.
Shor Algorithm: Circuit Details
Covers the details of the Shor algorithm circuit and its complexity.
Machine learning: Physics and Data
Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.