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GPU-accelerated fault dictionary generation for the TRAX fault model

机译:用于TRAX故障模型的GPU加速故障字典生成

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This paper presents the design and implementation of a fault simulator for the TRAnsition-X fault model (TRAX for short) on a graphics processing unit (GPU). Fault dictionaries are an important aspect of on-chip fault detection and diagnosis. Generating a fault dictionary requires fault simulation with no fault dropping, requiring extensive computational resources. The inherent parallelism of the fault simulation problem maps well to the large number of concurrent threads supported by a modern GPU, and a GPU can be used to accelerate the construction of a fault dictionary. Our approach employs both pattern-parallel and fault-parallel algorithms in the GPU kernel implementations. Experiments involving various circuits, including the OpenSPARC T2 processor, demonstrate a speed-up of over 42x.
机译:本文介绍了图形处理器(GPU)上TRAnsition-X故障模型(简称TRAX)的故障模拟器的设计和实现。故障字典是片上故障检测和诊断的重要方面。生成故障字典需要对故障进行仿真,而不会出现故障掉落,这需要大量的计算资源。故障仿真问题的固有并行性很好地映射到现代GPU支持的大量并发线程,并且GPU可用于加速故障字典的构建。我们的方法在GPU内核实现中同时采用了模式并行和故障并行算法。涉及各种电路(包括OpenSPARC T2处理器)的实验表明,速度提高了42倍以上。

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