问题
I have this tool called cgatools from complete genomics (http://cgatools.sourceforge.net/docs/1.8.0/). I need to run some genome analyses in High-Performance Computing Cluster. I tried to run the job allocating more than 50 cores and 250gb memory, but it only uses one core and limits the memory to less than 2GB. What would be my best option in this case? Is there a way to run binary executables in HPC cluster making it use all the allocated memory?
回答1:
The scheduler just runs the binary provided by you on the first node allocated. The onus of splitting the job and running it in parallel is on the binary. Hence, you see that you are using one core out of the fifty allocated.
Parallelising at the code level
You will need to make sure that the binary that you are submitting as a job to the cluster has some mechanism to understand the nodes that are allocated (interaction with the Job Scheduler) and a mechanism to utilize the allocated resources (MPI, PGAS etc.).
If it is parallelized, submitting the binary through a job submission script (through a wrapper like mpirun/mpiexec) should utilize all the allocated resources.
Running black box serial binaries in parallel
If not, the only other possible workload distribution mechanism across the resources is the data parallel mode, wherein, you use the cluster to supply multiple inputs to the same binary and run the processes in parallel to effectively reduce the time taken to solve the problem.
You can set the granularity based on the memory required for each run. For example, if each process needs 1GB of memory, you can run 16 processes per node (with assumed 16 cores and 16GB memory etc.)
The parallel submission of multiple inputs on a single node can be done through the tool Parallel. You can then submit multiple jobs to the cluster, with each job requesting 1 node (exclusive access and the parallel tool) and working on different input elements respectively.
If you do not want to launch 'n' separate jobs, you can use the mechanisms provided by the scheduler like blaunch to specify the machine on which the job is supposed to be run dynamically. You can parse the names of the machines allocated by the scheduler and further use blaunch like script to emulate the submission of n jobs from the first node.
Note: These class of applications are better off being run on a cloud like setup instead of typical HPC systems [effective utilization of the cluster at all the levels of available parallelism (cluster, thread and SIMD) is a key part of HPC.]
来源：https://stackoverflow.com/questions/34397199/how-to-run-binary-executables-in-multi-thread-hpc-cluster