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Assuming you have a 4-GPU setup, the GPUs will be numbered 0, 1, 2 and 3.In general, you most likely will want to run a single MPI process on each GPU.

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Using this option, they are all read into RAM once, at the very beginning of the job instead.On a 4-GPU development machine with 16 visible cores, we often run classifications or refinements using: Which produces 4 working (slave) mpi-ranks, each with 4 threads.This produces a single rank per card, but allows multiple CPU-cores to use each GPU, maximizing overall hardware utilization.It is only approximately half as slow as the Titan-X (Pascal), and beats 10 nodes on our cluster by almost a factor two!These machines are our standard GPU nodes on the cluster.Note: Reading the particles from our heavily used /beegfs shared file system is relatively slow.

Because 64GB of RAM is only just enough to read the entire data set (51GB) once, the two MPI slaves will have to get pre-read particles from the master (through ), or one has to run the non-MPI version of the program with different threads on each card.

wget ftp://ac.uk/pub/databases/emdb/structures/EMD-2660/map/emd_2660gz . gunzip emd_2660gz mpirun -n XXX `which relion_refine_mpi` --i Particles/shiny_2--ctf --iter 25 --tau2_fudge 2 --particle_diameter 360 --K 200 --zero_mask --oversampling 1 --psi_step 6 --offset_range 5 --offset_step 2 --norm --scale --random_seed 0 --o class2d mpirun -n XXX `which relion_refine_mpi` --i Particles/shiny_2--ref emd_2660.map:mrc --firstiter_cc --ini_high 60 --ctf --ctf_corrected_ref --iter 25 --tau2_fudge 4 --particle_diameter 360 --K 6 --flatten_solvent --zero_mask --oversampling 1 --healpix_order 2 --offset_range 5 --offset_step 2 --sym C1 --norm --scale --random_seed 0 --o class3d By default large messages are passed between MPI processes through reading and writing of large files on the computer disk.

By giving this option, the messages will be passed through the network instead. By default, all MPI slaves read their own particles (from disk or into RAM).

You can use an argument to the option to provide a list of device-indices.

The syntax is then to delimit ranks with colons [:], and threads by commas [,].

Each mpi-rank requires it’s own copy of large object in CPU and GPU memory, but if it can fit into memory it may in fact be faster to run 2 or more MPI processes on each GPU, as the MPI processes may become asynchronized so that one MPI process is busy doing calculations, while the other one for example is reading images from disk.