Major microprocessor vendors have integrated functional software-based self-testing in their manufacturing test flows during the last decade. Functional self-testing is performed by test programs that the processor executes atspeed from on-chip memory. Multiprocessors and multithreaded architectures are constantly becoming the typical general-purpose computing paradigm, and thus the various existing uniprocessor functional self-testing schemes must be adopted and adjusted to meet the testing requirements of complex multiprocessors. A major challenge in porting a functional self-testing approach from the uniprocessor to the multiprocessor case is to take advantage of the inherent execution parallelism offered by the multiple cores and the multiple threads in order to reduce test execution time. In this paper, we study the application of functional self-testing to chip multithreaded (CMT) processors. We propose a method that exploits thread-level parallelism (TLP) to speed up the execution of self-test routines in every physical core of a multiprocessor chip. The proposed method effectively splits the self-test routines into shorter ones, assigns the new routines to the hardware threads of the core and schedules their execution in order to minimize the core idle intervals due to cache misses or long latency operations and maximize the utilization of core computing resources. We demonstrate our method in the opensource CMT multiprocessor model, Sun's OpenSPARC T1, which contains eight CPU cores, each one supporting four hardware threads. Our experimental results show a self-test execution speedup of more than three times compared to the single thread execution.
Abstract|Built-in self-test (BIST) techniques have evolved as cost-eective techniques for testing digital circuits. These techniques add test circuitry to the chip such that the chip has the capability to test itself. A prime concern in using BIST is the area overhead due to the modication of normal registers to be test registers. This paper presents data path allocation algorithms that 1) maximize the sharing of test registers resulting in a fewer number of registers being modied for BIST, and 2) minimize the number of CBILBO registers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.