This is the webpage for the GIMPS.California team. Anyone is welcome to join. Please help us on the search for the next Mersenne prime!
If you are new to GIMPS, you can basically download the Prime95 zip file (bzip for Linux) and extract it and start it up. You should enter you PrimeNet user ID and computer name so that you get credit for the CPU hours that you have contributed. Otherwise they will go to the anonymous account.
I highly suggest you modify the Worker Windows menu to take advantage of mutiple cores that you have in your processor. You can change the “Number of worker windows to run” from the default of 1 to 3 or more, and then specify the number of cores used per worker.
I have found that running LL or LL Double check or PRP tests using Prime95 is not that effective. Most people nowadays will have a decent NVIDIA graphics cards, and if you do, it’s better (faster) to use CUDALucas for LL or double check tests – I’ll describe below. otherwise, I highly recommend doing P-1 factoring, or “ECM for first factors of Mersenne numbers”, and lastly “Trial factoring to low limits”. Also Trial factoring is much, much fast using CUDA cores instead of a CPU in Prime95.
Basically if you have a fairly new NVIDIA card (i.e. GTX 1060), you run Lucas-Lehmer tests with your graphics card using the CUDALucas prebuilt application. Go to https://sourceforge.net/projects/cudalucas/ and download the latest. For example for Windows, as of today it is “CUDALucas2.06-CUDA4.0-10.1-Windows32.64.7z”, you will also need the libraries, and they should be extracted to the same directory.
After installing CUDALucas, you need to run the self tests. You should first run the “-cufftbench” and “-threadbench” self-tests so the CUDALucas will automtically select the right FFT and thread values for your graphic card for the particular exponent that you are testing. These self-tests can take a long time to run the first time, but are you run them once, that’s all you need.
You can use the application Mfacktc with a fairly new NVIDA graphics card to do Trial Factoring using CUDA cores. The effectiveness of using a NVIDIA is that you can very quickly process exponents using CUDA cores. The latest pre-built mfaktc binaries for Windows and Linux are located here: https://download.mersenne.ca/mfaktc/mfaktc-0.21 . Just download and unzip and follow instructions.