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I forgot to ask, I'm not too familiar with the inner workings of CUDA (working on that.) Does increasing the WU size decrease performance?

Picch wrote:I forgot to ask, I'm not too familiar with the inner workings of CUDA (working on that.) Does increasing the WU size decrease performance?

It's not actually a CUDA thing, it's a "my code" thing.

Larger workunits don't hurt performance. If anything, they help it.

The only time larger workunits would hurt performance is if you have multiple GPUs and you increase the workunit size so large that not all the GPUs can remain "fed."

So, if you set the workunit size so long that you can only have 3 workunits in your problem set but there are 4 GPU cores, the 4th core will not be used (as there is nothing for it to do).

Any update on releasing the OSX build of the latest Alpha? I'd like to test out some of the new features!

Thanks again!

I was wondering if there was any new news regarding releasing an osx version. I am really excited to use the new salted feature. Thanks

"Source is out there, have a ball with the build process"?

I'll see if I can get an OS X build working. It may take a few iterations to properly bundle all the files. Are you willing to test some betas on a non-dev OS X box & see if things work?

Thats great news. I would definitely be willing to test the beta for a non-dev os x computer. Also idk if you want help, but I am pretty decent at coding. I know c, objective c, c++, java, python, among other things. Thanks for the quick reply

Shameless bump for release of OSX alpha! And yeah, I wouldn't mind running any tests you'd like done.

Cool. I'll see what I can do.

I've been focusing on the rainbow table side of things lately, but just picked up a spiffy new dev laptop (well... netbook). I'm hoping to get my different build environments hammered out in the near future so I can actually do multi-OS builds easily.

Hi,
great work!

I was trying .80alpha4 on my Intel QuadCore with a nVidia GT9800 + GTX 295 on a NTLM hash (one single hash) as soon as the password length tried arrives to 3 I get the following error: Cuda error: too many resources requested for launch./s

It's the same with alpha3

I got it working adding --bits 14...
now I get this error:
out of WU.Charset does not extend to password length 9!

my command line is
./CUDA-Multiforcer-CPP -l -h NTLM -f ./test_hashes/Hashes-NTLM-Full.txt --min=1 --max=10 -u ./charsets/charset-all-multi --bits 14

albatr0ss wrote:I was trying .80alpha4 on my Intel QuadCore with a nVidia GT9800 + GTX 295 on a NTLM hash (one single hash) as soon as the password length tried arrives to 3 I get the following error: Cuda error: too many resources requested for launch./s

Alright, this may be a "my bad" in testing. I haven't had an 8800 in place in a while...

Try passing "--threads 256" - it attempts to auto-tune the block/thread count, and I may have assigned too many threads by default to the G80/G92 cores.

I got it working adding --bits 14...
now I get this error:
out of WU.Charset does not extend to password length 9!

my command line is
./CUDA-Multiforcer-CPP -l -h NTLM -f ./test_hashes/Hashes-NTLM-Full.txt --min=1 --max=10 -u ./charsets/charset-all-multi --bits 14

--bits 14 shouldn't have *anything* to do with the CUDA out of resources error... I really don't know why that fixes it.

The "Charset does not extend to password length 9" error is likely because charset-all-multi most likely only has 8 lines - you need one line per position for the per-position charset stuff.