Power Modeling and Scheduling of Tests for Core-based System Chips

Abstract: The technology today makes it possible to integrate a complete system on a single chip, called "System-on-Chip'' (SOC). Nowadays SOC designers use previously designed hardware modules, called cores, together with their user defined logic (UDL), to form a complete system on a single chip. The manufacturing process may result in defect chips, for instance due to the base material, and therefore testing chips after production is important in order to ensure fault-free chips. The testing time for a chip will affect its final cost. Thus it is important to minimize the testing time for each chip. For core-based SOCs this can be done by testing several cores at the same time, instead of testing the cores sequentially. However, this will result in a higher activity in the chip, hence higher power consumption. Due to several factors in the manufacturing process there are limitations of the power consumption for a chip. Therefore, the power limitations should be carefully considered when planning the testing of a chip. Otherwise it can be damaged during test, due to overheating. This leads to the problem of minimizing testing time under such power constraints. In this thesis we discuss test power modeling and its application to SOC testing. We present previous work in this area and conclude that current power modeling techniques in SOC testing are rather pessimistic. We therefore propose a more accurate power model that is based on the analysis of the test data. Furthermore, we present techniques for test pattern reordering, with the objective of partitioning the test power consumption into low parts and high parts. The power model is included in a tool for SOC test architecture design and test scheduling, where the scheduling heuristic is designed for SOCs with fixed- width test bus architectures. Several experiments have been conducted in order to evaluate the proposed approaches. The results show that, by using the presented power modeling techniques in test scheduling algorithms, we will get lower testing times and thus lower test cost.