6 Mar. 2009 ArDean Leith
While getting ready to retire a bunch of old SGI MIPS based servers and workstations, I wondered how much faster our current AMD Opteron 64 bit Linux boxes are than our trusted old machines of 5-10 years ago. Benchmark table.
11 Feb. 2009 ArDean Leith
If you are using a Beowulf type cluster for parallel execution of time consuming operations during single particle reconstruction, there are three common methods of parallelizing discussed on our website. Since the iterative alignment and defocus group backprojection steps typically consume more than 98% of the compute time and are trivially parallelizable by defocus group, we commonly use a simple PubSub script for distributing jobs to different compute nodes. Other sites have their own scripts to handle the distribution. However if you have a inexpensive cluster with simple Ethernet networking this method has a large inefficiency when there are many nodes accessing a single storage disk or simple RAID array on a file server using NFS mounts from the compute nodes.
When many compute nodes attempt to access a single disk (or RAID array) using NFS there is a significant slowdown in overall through put. There is a lot of effort currently to overcome this problem with various methods e.g. Parallel NFS. However if your compute nodes include adequate local storage on all the nodes there is a simple solution that may improve through-put. At the beginning of a compute node computation, copy all the files that are accessed to the local disk with a systems call, then carry out the computations. At the end of the compute nodes processing, copy any altered files back to the file server.
We have recently altered the scripts that we use during the projection matching step of 3D Reconstruction so that pub_refine.pam and its associated procedures (especially pub_refine_start.pam) handle the cloning of the necessary files on local compute nodes and the transmission back to the server at the end of the processiong on the compute nodes.
On our compute cluster this modification is very productive. The speed increase will of course depend on the number of simultaneous processes, and the pattern of disk access.
Source: random.html Page updated: 25 Oct. 09 ArDean Leith