International Business Machines Corporation

Dwayne A Lowe

Michael Charles Elles

Tu T Dang

Juan Q Hernandez

Challis Llewellyn Purrington

Sumanta Kumar Bahali

Michael Leo Scollard

Ivan R Zapata

Challis L Purrington, Sr

One embodiment provides a method for scalable predictive failure analysis. Embodiments of the method may include gathering memory information for memory on a user computer system having at least one processor. Further, the method includes selecting one or more memory-related parameters. Further still, the method includes calculating based on the gathering and the selecting, a single bit error value for the scalable predictive failure analysis through calculations for each of the one or more memory-related parameters that utilize the memory information. Yet further, the method includes setting, based on the calculating, the single bit error value for the user computer system.

Scalable prediction failure analysis for memory used in modern computers

One embodiment provides an error detection method wherein single-bit errors in a memory module are detected and identified as being a random error or a repeat error. Each identified random error and each identified repeat error occurring in a time interval is counted. An alert is generated in response to a number of identified random errors reaching a random-error threshold or a number of identified repeat errors reaching a repeat-error threshold during the predefined interval. The repeat-error threshold is set lower than the random-error threshold. A hashing process may be applied to the memory address of each detected error to map the location of the error in the memory system to a corresponding location in an electronic table.

Use of hashing function to distinguish random and repeat errors in a memory system

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Durham, NC, United States of America

Dwayne A Lowe