A Fast and Accurate Analytical Technique to Compute the AVF of Sequential Bits in a Processor

The rate of particle induced soft errors in a processor increases in proportion to the number of bits. This soft error rate (SER) can limit the performance of a system by placing an effective limit on the number of cores, nodes or clusters. The vulnerability of bits in a processor to soft errors can be represented by their architectural vulnerability factor (AVF), defined as the probability that a bit corruption results in a user-visible error. Analytical models such as architecturally correct execution (ACE) lifetime analysis enable AVF estimation at high speed by operating at a level of abstraction well above that of RTL. However, sequential elements do not lend themselves to this type of analysis because these bits are not typically included in the abstracted ACE model. Brute force methods, such as statistical fault injection (SFI), enable register level detail but at the expense of computation speed. We have developed a novel approach that marries the computational speed of the analytical approach with the level of detail of the brute force approach. Our methodology introduces the concept of “port AVFs” computed by ACE analysis on a performance model and applies these values to a node graph extracted from RTL. We employ rules derived from set theory that let us propagate these port AVFs throughout the node graph using an iterative relaxation technique. This enables us to generate statistically significant AVFs for all sequential nodes in a given processor design in a fast and accurate manner. We use this approach to compute the sequential AVF for all nodes in a modern microprocessor and show good correlation with beam test measurements on silicon.