Let's say, I've got a 4-core CPU, which basically means, my computer could run 4 processes at the same time; no more no less.
Now let's look at cluster module of nodejs; there are
1 master process
4 worker processes
Can I say, each worker process is to be assigned to each core of the CPU?
And if it is, then where is its master process located?
The master process is fired as a standard single-thread process (or service) so it "is assigned to" and lives on one of your CPU cores (or threads, depending on the case).
Each worker process is then spawned (forked) as described in the docs:
https://nodejs.org/api/cluster.html
Just so you know, Node now supports the use of worker_threads to execute JavaScript in parallel on multiple threads, so it's technically not true anymore that Node is limited by single-thread execution:
https://nodejs.org/api/worker_threads.html
Related
I developed a Python script that enables multiple-threads. I sent my code to Slurm. I would like to verify if the multiple threads work well.
Therefore I want to monitor the real-time CPUs' usage. Is there any command can do this?
Most clusters allow logins to nodes if the user has a job running on it. So, just ssh to the node that is running your job, and run top(1)
If your code is multithreaded, the value in the %CPU column should be greater than 100%. Each thread, if it is fully busy, can consume up to 100% CPU (i.e. all the cycles on a single CPU core). So, N threads can consume up to N*100%.
I built a Node.js application that is built up of smaller components (children worker processes) that all perform different tasks, “in parallel”. When the main program runs, it spawns the workers and they begin their work. I used Node.js’s cluster module to accomplish this.
Is this an example of multiprocessing or parallel processing, and why?
Clustering is better to say a load balancer rather than parallel processing.
Node JS is single threaded, it means if you have 4 cores, it will use one regardless of available cores, that's fork mode, Clustering uses one node thread on all available cores, that's an optimized way of doing things and load balancing.
I have 2 node.js programs that communicate with each other through a socket. I originally intended on running them on separate linux machines, but realized it would be much simpler to have them both on one multi-core machine, each allocated a specific subset of the total CPUs. For example, I have a machine with 8 cores, I want to run program_A on 2 cores as 1 process (using node's fork module), and program_B on the remaining 6 cores, also as a single process forked over several cores. Is there any way to do this with node.js? I'm aware of taskset to set CPU affinity, but I'm not quite sure if that would work for this scenario.
When utilizing multi cores via Node.js' cluster module is it guaranteed that each forked node worker is assigned to a different core?
If it's not guaranteed is there any way to control or manage it and eventually guarantee that all end up in different cores? Or the OS' scheduler distributes them evenly?
A while ago I did some tests with cluster module which you can check in this post that I wrote. Looking at the system monitor screenshots it is this pretty straightforward to understand what happens under the hood (with and without cluster module).
It is indeed up to the OS to distribute processes over the cores. You could obtain the pid of a child process and use an external utility to set the CPU affinity of that process. That would, of course, not be very portable.
What happens if I would try to run a multithreaded job in 1 SGE slot? Would it fail to start multiple threads? Or would it still start these multiple threads and potentially overload the SGE cluster node, because it is going to run more threads than there are slots?
I know I should use the -pe threaded nrThreads parameter. But I am running a program of which I am not sure how many threads it is using for every step.
It's been a while since I've used SGE, but at least back then, a job which launched more computational threads than allocated would not be prevented from launching those threads, usually then stealing CPU time from other jobs.
Perhaps current SGE versions are capable of using cpusets, which allow the administrator to limit the CPU's used by a job. At least the slurm scheduler can do this.