Power-aware system-on-chip test scheduling using enhanced rectangle packing algorithm

2012 ◽  
Vol 38 (6) ◽  
pp. 1444-1455 ◽  
Author(s):  
Chia Yee Ooi ◽  
Jia Pao Sua ◽  
Siaw Chen Lee
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.


2019 ◽  
Vol 32 (9) ◽  
pp. 5303-5312 ◽  
Author(s):  
Gokul Chandrasekaran ◽  
Sakthivel Periyasamy ◽  
Karthikeyan Panjappagounder Rajamanickam

2019 ◽  
Vol 1 (9) ◽  
Author(s):  
Gokul Chandrasekaran ◽  
Sakthivel Periyasamy ◽  
P. R. Karthikeyan

2010 ◽  
Vol 663-665 ◽  
pp. 670-673
Author(s):  
Zhong Liang Pan ◽  
Ling Chen

The main aspects for the test of system on chip (SoC) are designing testability architectures and solving the test scheduling. The test time of SoC can be reduced by using good test scheduling schemes. A test scheduling method based on cellular genetic algorithm is presented in this paper. In the method, the individuals are used to represent the feasible solutions of the test scheduling problem, the individuals are distributed over a grid or connected graph, the genetic operations such as selection and mutation are applied locally in some neighborhood of each individual. The test scheduling schemes are obtained by carrying out the evolutionary operations for the populations. A lot of experiments are performed for the SoC benchmark circuits, the experimental results show that the better test scheduling schemes can be obtained by the method in this paper.


Author(s):  
HAIDAR M. HARMANANI ◽  
HASSAN A. SALAMY

This paper presents an efficient method to determine minimum system-on-chip (SOC) test schedules with precedence and power constraints based on simulated annealing. The problem is solved using a partitioned testing scheme with run to completion that minimizes the number of idle test slots. The method can handle SOC test scheduling with and without power constraints in addition to precedence constraints that preserve desirable orderings among tests. We present experimental results for various SOC examples that demonstrate the effectiveness of the method. The method achieved optimal test schedules in all attempted cases in a short CPU time.


Author(s):  
Wissam Marrouche ◽  
Rana Farah ◽  
Haidar M. Harmanani

System-on-chip (SOC) has become a mainstream design practice that integrates intellectual property cores on a single chip. The SOC test scheduling problem maximizes the simultaneous test of all cores by determining the order in which various cores are tested. The problem is tightly coupled with the test access mechanism (TAM) bandwidth and wrapper design. This paper presents a strength Pareto evolutionary algorithm for the SOC test scheduling problem with the objective of minimizing the power-constrained test application time, wrapper design and TAM assignment in flat and hierarchical core-based systems. We demonstrate the effectiveness of the method using the ITC’02 benchmarks.


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