This is interesting stuff. Think back a few years when we were talking about checkpoint/restart issues: as the scale of your problem gets bigger, the time to checkpoint becomes bigger than the time actually doing useful work. And, of course, the reason we do checkpoint/restart is because it’s bare-metal and easy. Just like simple message passing is “close to the metal” and “straightforward”.
Similarly, there’s “fine grained” error detection and correction: ECC codes in memory; redundant comm links or retries. Each of them imposes some speed/performance penalty (it takes some non-zero time to compute the syndrome bits in a ECC, and some non-zero time to fix the errored bits… in a lot of systems these days, that might be buried in a pipeline, but the delay is there, and affects performance) I think of ECC as a sort of diffuse fault management: it’s pervasive, uniform, and the performance penalty is applied evenly through the system. Redundant (in the TMR sense) links are the same way. Retries are a bit different. The “detecting” a fault is diffuse and pervasive (e.g. CRC checks occur on each message), but the correction of the fault is discrete and consumes resources at that time. In a system with tight time coupling (a pipelined systolic array would be the sort of worst case), many nodes have to wait to fix the one that failed. A lot depends on the application: tighter time coupling is worse than embarrassingly parallel (which is what a lot of the “big data” stuff is: fundamentally EP, scatter the requests, run in parallel, gather the results). The challenge is doing stuff in between: You may have a flock with excess capacity (just as ECC memory might have 1.5N physical storage bits to be used to store N bits), but how do you automatically distribute the resources to be failure tolerant. The original post in the thread points out that MPI is not a particularly facile tool for doing this. But I’m not sure that there is a tool, and I’m not sure that MPI is the root of the lack of tools. I think it’s that moving from close to the metal is a “hard problem” to do in a generic way. (The issues about 32 bit counts are valid, though) James Lux, P.E. Task Manager, DHFR Space Testbed Jet Propulsion Laboratory 4800 Oak Grove Drive, MS 161-213 Pasadena CA 91109 +1(818)354-2075 +1(818)395-2714 (cell)
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