HARP: Practically and Effectively Identifying Uncorrectable Errors in Memory Chips That Use On-Die Error-Correcting Codes

Aggressive storage density scaling in modern main memories causes increasing error rates that are addressed using error-mitigation techniques. State-of-the-art techniques for addressing high error rates identify and repair bits that are at risk of error from within the memory controller. Unfortunately, modern main memory chips internally use on-die error correcting codes (on-die ECC) that obfuscate the memory controller's view of errors, complicating the process of identifying at-risk bits (i.e., error profiling).

To understand the problems that on-die ECC causes for error profiling, we analytically study how on-die ECC changes the way that memory errors appear outside of the memory chip (e.g., to the memory controller). We show that on-die ECC introduces statistical dependence between errors in different bit positions, raising three key challenges for practical and effective error profiling: on-die ECC (1) exponentially increases the number of at-risk bits the profiler must identify; (2) makes individual at-risk bits more difficult to identify; and (3) interferes with commonly-used memory data patterns that are designed to make at-risk bits easier to identify.

To address the three challenges, we introduce Hybrid Active-Reactive Profiling (HARP), a new error profiling algorithm that rapidly achieves full coverage of at-risk bits based on two key insights. First, errors that on-die ECC fails to correct have two sources: (1) direct errors from raw bit errors in the data portion of the ECC word and (2) indirect errors that on-die ECC introduces when facing uncorrectable errors. Second, the maximum number of indirect errors that can occur concurrently is limited to the correction capability of on-die ECC. HARP's key idea is to first identify all bits at risk of direct errors using existing profiling techniques with the help of small modifications to the on-die ECC mechanism. Then, a secondary ECC within the memory controller with correction capability equal to or greater than that of on-die ECC can safely identify bits at-risk of indirect errors, if and when they fail.

We evaluate HARP in simulation relative to two state-of-the-art baseline error profiling algorithms. We show that HARP achieves full coverage of all at-risk bits faster (e.g., 99th-percentile coverage 20.6%/36.4%/52.9%/62.1% faster, on average, given 2/3/4/5 raw bit errors per ECC word) than the baseline algorithms, which sometimes fail to achieve full coverage. We perform a case study of how each