01-19-2014, 02:46 AM
Specifics on the underlying protocol and authentication mechanisms, please.
There appears to be two assumptions with the -s/-l mechanics:
1) The password lists are relatively small; and,
2) Data flow (i.e. network usage) is relatively minimal.
Without documentation on the mechanics of -s and -l then I have to ask: How skipping is achieved? Assuming the words aren't sorted and indexed, I assume skipping is achieved by reading the list because you don't know where to seek(). On a 1TB file, for example, that could mean most of the file would have to be read before submission to the last GPU, resulting in two problems:
1) Ramp-up is a slow linear step (i.e., node start up, network xfr contention, etc.); and,
2) It may be possible that GPU set #1 is long finished before GPU set #7 is started.
It's not clear to me from the posting whether a central node is distributing chunks of work or you're running oclHashcat manually on each node. The later is not good because a 100MB list across ten equal GPU sets means a rough network bandwidth consumption of 500MB.
My use cases are probably different that others. In my case, I have precomputed password lists whereas others are probably running rules against small lists. In my case I have >50TB of data.
There appears to be two assumptions with the -s/-l mechanics:
1) The password lists are relatively small; and,
2) Data flow (i.e. network usage) is relatively minimal.
Without documentation on the mechanics of -s and -l then I have to ask: How skipping is achieved? Assuming the words aren't sorted and indexed, I assume skipping is achieved by reading the list because you don't know where to seek(). On a 1TB file, for example, that could mean most of the file would have to be read before submission to the last GPU, resulting in two problems:
1) Ramp-up is a slow linear step (i.e., node start up, network xfr contention, etc.); and,
2) It may be possible that GPU set #1 is long finished before GPU set #7 is started.
It's not clear to me from the posting whether a central node is distributing chunks of work or you're running oclHashcat manually on each node. The later is not good because a 100MB list across ten equal GPU sets means a rough network bandwidth consumption of 500MB.
My use cases are probably different that others. In my case, I have precomputed password lists whereas others are probably running rules against small lists. In my case I have >50TB of data.