Multicast Test Architecture and Test Scheduling for Interposer-Based 2.5D ICs

Author(s):  
Shengcheng Wang ◽  
Ran Wang ◽  
Krishnendu Chakrabarty ◽  
Mehdi B. Tahoori
Author(s):  
B. Noia ◽  
K. Chakrabarty ◽  
S. K. Goel ◽  
E. J. Marinissen ◽  
J. Verbree

Author(s):  
Rudolf Schlangen ◽  
Jon Colburn ◽  
Joe Sarmiento ◽  
Bala Tarun Nelapatla ◽  
Puneet Gupta

Abstract Driven by the need for higher test-compression, increasingly many chip-makers are adopting new DFT architectures such as “Extreme-Compression” (XTR, supported by Synopsys) with on-chip pattern generation and MISR based compression of chain output data. This paper discusses test-loop requirements in general and gives Advantest 93k specific guidelines on test-pattern release and ATE setup necessary to enable the most established EFA techniques such as LVP and SDL (aka DLS, LADA) within the XTR test architecture.


2020 ◽  
pp. 1-13
Author(s):  
Gokul Chandrasekaran ◽  
P.R. Karthikeyan ◽  
Neelam Sanjeev Kumar ◽  
Vanchinathan Kumarasamy

Test scheduling of System-on-Chip (SoC) is a major problem solved by various optimization techniques to minimize the cost and testing time. In this paper, we propose the application of Dragonfly and Ant Lion Optimization algorithms to minimize the test cost and test time of SoC. The swarm behavior of dragonfly and hunting behavior of Ant Lion optimization methods are used to optimize the scheduling time in the benchmark circuits. The proposed algorithms are tested on p22810 and d695 ITC’02 SoC benchmark circuits. The results of the proposed algorithms are compared with other algorithms like Ant Colony Optimization, Modified Ant Colony Optimization, Artificial Bee Colony, Modified Artificial Bee Colony, Firefly, Modified Firefly, and BAT algorithms to highlight the benefits of test time minimization. It is observed that the test time obtained for Dragonfly and Ant Lion optimization algorithms is 0.013188 Sec for D695, 0.013515 Sec for P22810, and 0.013432 Sec for D695, 0.013711 Sec for P22810 respectively with TAM Width of 64, which is less as compared to the other well-known optimization algorithms.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Umair Saeed Solangi ◽  
Muhammad Ibtesam ◽  
Muhammad Adil Ansari ◽  
Jinuk Kim ◽  
Sungju Park

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