Arvind Jain

Test Schedule Optimization for Multicore SoCs: Handling Dynamic Voltage Scaling and Multiple Voltage Islands

In order to provide high performance with low power consumption, many multicore chips employ dynamic voltage scaling and voltage islands that operate at multiple power-supply voltage levels. Effective defect screening for such chips requires test applications at different operating voltages, which leads to higher test time and test cost compared to systems-on-a-chip (SoCs), which operate at only a single voltage level. We propose test scheduling techniques to minimize the testing time for multicore chips when each core is tested at multiple voltage levels and when it is tested for state retention when the core switches between two voltage levels. The proposed techniques include exact optimization based on integer linear programming and fast heuristic methods. Experimental results for two test-case SoCs from the industry highlight the effectiveness of the proposed method.

Test Scheduling for Multicore SoCs with Dynamic Voltage Scaling and Multiple Voltage Islands

In order to provide high performance with low power consumption, modern multicore chips employ dynamic voltage scaling and voltage islands that operate at multiple power-supply voltage settings. Effective defect screening for the embedded cores in such multicore chips requires test application at their different operating voltages, which leads to higher test time and test cost. We propose a fast heuristic test scheduling technique for multicore chips that minimize the testing time when each core is tested at multiple voltage settings as well as if it is tested for state retention when the core switches between two voltage levels. Experimental results for two test-case SOCs from industry highlight the effectiveness of the proposed method.

Time-division multiplexing for testing SoCs with DVS and multiple voltage islands

Dynamic voltage scaling (DVS) has been widely adopted in multicore SoCs for reducing dynamic power consumption. Despite its benefits, the use of DVS increases test time because high product quality can only be ensured by testing every core at multiple supported voltage settings; hence the repetitive application of the same or different tests at multiple voltage settings becomes necessary. In addition, testing at lower supply voltage settings increases considerably the length of each test because lower scan frequencies must be used for shifting test data using scan chains. Standard scheduling techniques fail to reduce the test time for DVS-based SoCs since they do not model testing at multiple voltage settings. In addition, they do not consider the practical aspects of tester overhead and the dependencies between core voltage settings due to the use of voltage islands. To alleviate the detrimental impact of DVS on test application time, we propose a time-division multiplexing (TDM) method and an integer linear programming-based test scheduling technique, which exploit high automatic test equipment (ATE) frequencies even when low shift frequencies must be used at low voltage settings. Experimental results on two industrial SoCs highlight the effectiveness of TDM and the associated scheduling method.

Time-Division Multiplexing for Testing DVFS-Based SoCs

Dynamic voltage-frequency scaling (DVFS) is used in system-on-chips (SoCs) for power management, but it increases test time because every core must be tested at multiple voltage settings. In addition, testing at lower power supply voltage settings increases the length of each test due to the corresponding reduction in frequencies that can be used for scan shift operations. Existing test scheduling techniques do not consider test applications at multiple voltage settings, therefore they are not effective for reducing test time for DVFS-based SoCs. We propose a time-division multiplexing (TDM) architecture, which uses the highest available frequency for shifting test data into the SoC and then distributes the test data into multiple cores using lower shift frequencies. TDM is accompanied by three test scheduling methods, which are suitable for different scenarios: 1) an integer linear programming-based formulation that offers optimal results for SOCs of moderate size; 2) a greedy approach that provides good results with very short run time even for very large SoCs; and 3) a rectangle-packing approach combined with simulated-annealing that offers a trade-off between run time and test-time reduction for all SoCs. Experimental results on two industrial SoCs highlight the effectiveness of TDM and the associated scheduling methods.

Multi-site test optimization for multi-V dd SoCs using space- and time- division multiplexing

Even though system-on-chip (SoC) testing at multiple voltage settings significantly increases test complexity, the use of a different shift frequency at each voltage setting offers parallelism that can be exploited by time-division multiplexing (TDM) to reduce test length. We show that TDM is especially effective for small-bitwidth and heavily loaded test-access mechanisms (TAMs), thereby tangibly increasing the effectiveness of multi-site testing. However, TDM suffers from some inherent limitations that do not allow the fullest possible exploitation of TAM bandwidth. To overcome these limitations, we propose space-division multiplexing (SDM), which complements TDM and offers higher multi-site test efficiency. We implement space-and time-division multiplexing (STDM) using a new, scalable test-time minimization method based on a combination of bin packing and simulated annealing. Results for industrial SoCs, highlight the advantages of the proposed optimization method.

Multi-CoDec Configurations for Low Power and High Quality Scan Test

Scan compression techniques are widely used to contain test application time and test data volume. Smart techniques exist to match the scan compression CoDec (compactor-decompressor) module with the DUT (design under test), to realize high levels of compression with no loss of coverage. DUT partitioning is often desirable for ease of implementing sub-chips and integrating them into an SOC (system-on-chip). This paper presents various multi-CoDec configurations for partitioned DUTs to enable efficient scan testing, which address the requirements of reduced test mode power with no compromise in test quality. Different configurations are examined, tradeoffs discussed, and the most suitable one amongst them identified. It is shown how the preferred configuration can be architected with low implementation overhead (with no new requirements for bounding when creating the individual partitions), and how the different CoDec – DUT partitions can be operated together to meet dual goals of high quality and low power, with no increase in test time. Experimental data is presented on industrial circuits to illustrate the benefits.

At-speed Testing of Asynchronous Reset De-assertion Faults

In sub-threshold technology nodes, device failure due to timing related defects (setup & hold timing) is on rise due to extreme process variability and increasing use of voltage scaling techniques for achieving required performance. High coverage using stuck-at fault patterns, which can effectively screen static defects is no longer sufficient to control DPPM (Defective parts per million). High test coverage of timing defects that is induced by process variation is required for controlling DPPM. Lot of work has been done to find the ways to increase the delay test coverage of industrial circuits including the various methods to cover inter-domain clock faults but very little or no work is done on the ways to effectively cover the asynchronous reset paths to the memory registers for timing defects. In this paper we propose a novel methodology that allows us to effectively detect the failures induced by timing defects on asynchronous reset path of the registers. This problem is further complicated by the fact that commercially available ATPG tools are not capable of generating test patterns due to modeling limitations. Results from 45nm industrial multi-million gates design is presented to illustrate the effectiveness of the proposed methodology.