Volume 8 Number 2 (Feb. 2013)
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JCP 2013 Vol.8(2): 517-524 ISSN: 1796-203X
doi: 10.4304/jcp.8.2.517-524

Design and Optimization of Test Architecture for IP Cores on SoC Based on Multi-objective Genetic Algorithm

Enmin Tan and Peng Wang
Guilin University of Electronic Technology, Guilin, China

Abstract—For system-on-chip (SoC) test based on IP cores integration reuse, the IEEE 1500 Standard has given specific testing architecture. In this paper, we aim at building controllable test architecture for IP cores on SoC based on IEEE 1500 Standard. The technique applied is referred to as test control switch which is configured to the Wrapper of IP cores. We design a switch control register (SCR) to configure the state of the switches, and apply the expanded TAP (eTAP) based on IEEE 1149.1 Standard to control the SCR and the Wrapper of IP cores. In addition, we design the chip level test control architecture which can be widely used for test of SoC based on IP cores. Finally, we apply the software of Modelsim to implement simulation about the control mechanism of the SCR and the eTAP. The simulation results show the effectiveness and controllability of the test architecture Besides, the paper builds SoC self-testing architecture through connecting Built-In-Self-Test (BIST) and IEEE 1500 Standard. The technique applied is referred to as Niche Genetic Algorithm (NGA) which is one of Multiobjective Genetic Algorithm, we build Block testing model which is optimization for partition of Testing-Access- Mechanisms (TAM) and IP cores based on NGA. The studies we have performed showed that the NGA can reduce SoC testing time effectively and the Block testing model can achieve testing data sharing for multiple IP cores.

Index Terms—IEEE 1500 Standard, SoC, Test Control Switch, Switch Control Register, expanded TAP, TAM, NGA

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Cite: Enmin Tan and Peng Wang, " Design and Optimization of Test Architecture for IP Cores on SoC Based on Multi-objective Genetic Algorithm," Journal of Computers vol. 8, no. 2, pp. 517-524, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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