From Gates to SDCs: Understanding Fault Propagation Through the Compute Stack
Odysseas Chatzopoulos, George N. Papadimitriou, Dimitris Gizopoulos, Harish Dattatraya Dixit, Sriram Sankar · 2025
Silent Data Corruption (SDC) is the most severe effect of a silicon defect in a CPU or other computing chip. The arithmetic units of a CPU are, usually, unprotected and are, thus, the ones that most likely produce SDCs (as well as visible malfunctions of programs such as crashes). In this work, we shed light on the traversal of silicon defects from their point of origin deep inside arithmetic units of complex CPUs towards the program result. We employ microarchitecture-level fault injection enhanced with gate-level designs of the arithmetic units of interest. The hybrid setup combines (i) the accuracy of the hardware and fault modeling and (ii) the speed of program simulation to run long programs to end (thus observing SDC incidents); the analysis that this combination delivers is impossible at other abstraction layers which are either hardware-agnostic (software level) or extremely slow (gate-level). We quantify the effects of faults in two stages and with multiple metrics: (a) how faults propagate to the outputs of the arithmetic units when individual instructions are executed, and (b) how faults eventually affect the outcome of the program generating SDCs, crashes, or being masked. Our fine-grain findings can be utilized for informed fault detection and tolerance strategies at the hardware or the software levels.