Today's computer architectures and semiconductor technologies are facing major challenges making them incapable to deliver the required features (such as computer efficiency) for emerging applications. Alternative architectures are being under investigation in order to continue deliver sustainable benefits for the foreseeable future society at affordable cost. These architectures are not only changing the traditional computing paradigm (e.g., in terms of programming models, compilers, circuit design), but also setting up new challenges and opportunities concerning the test and reliability. This tutorial targets the challenges and opportunities of using approximate computing for achieving low cost fault tolerance mechanisms.

This work presents an approximate triple modular redundancy (ATMR) method based on successive approximation and loop perforation. Successive approximation consists of loop-based algorithms that improve their output quality on every iteration execution. By manipulating the number of executed iterations, a designer can balance output quality and execution time performance. The proposed technique exploits this approximate computing paradigm combined with data size and precision reduction to minimize traditional triple modular redundancy (TMR) costs while maintaining a good fault masking capability. A number of ATMR configurations are presented and tested under laser fault injection to evaluate their fault masking capability. The benchmarks are implemented as embedded software in the ARM Cortex A9 processor of a Xilinx Zynq-7000 series board. The proposed technique was able to improve the execution time overhead with the usage of approximations, with an acceptable fault masking rate.

Today's computer architectures and semiconductor technologies are facing major challenges making them incapable to deliver the required features (such as computer efficiency) for emerging applications. Alternative architectures are being under investigation in order to continue deliver sustainable benefits for the foreseeable future society at affordable cost. These architectures are not only changing the traditional computing paradigm (e.g., in terms of programming models, compilers, circuit design), but also setting up new challenges and directions on the way these architectures should be tested to guarantee the required quality and reliability levels. This paper highlights the major open questions regarding test and reliability of three emerging computing paradigms being approximate computing, computation-in-memory and neuromorphic computing.