Heuristic algorithm for load balancing among threads

Question

I'm working on a multi-threaded program where I have a number of worker threads performing tasks of unequal length. I want to load-balance the tasks to ensure that they do roughly the same amount of work. For each task T_i I have a number c_i which provides a good approximation to the amount of work that is required for that task.

I'm looking for an efficient (O(N) N = number of tasks or better) algorithm which will give me "roughly" a good load balance given the values of c_i. It doesn't have to be optimal, but I would like to be able to have some theoretical bounds on how bad the resulting allocations are.

Any ideas?

Answer 1

You want to implement a work stealing algorithm. Each worker thread has a double ended queue, new tasks are added to the bottom of the smallest queue. Workers remove tasks from the top of their own queue (the top/bottom separation reduces contention), when a worker has no more jobs to do, it steals a job off the bottom of the largest queue. It's simple, and works well, this is the algorithm which the Microsoft parallel system coming with .net4.0 is based on I believe.

The resulting allocation is pretty good, worker threads will only be left with no work to do if there are no more jobs available in the entire system.

Nb. If you want some example code to tear apart, my friend wrote a work stealing system for C#, which you can find here

Answer 2

My inclination is not to try to figure out ahead of time how to assign the tasks, but to throw them all into a common work queue. Any worker thread with nothing else to do grabs the next task from the queue does the work and checks the queue for the next task.

Answer 3

Simplest way is to sort jobs descending by p_i (but this is O(n log n)) and do this:

1. For each thread we have est. run time e_n = 0.
2. For each task i find thread that has minimal e_n enque task on it and e_n = e_n + p_i.

This algorithm should give you best results but with O(NM) time where N is number of tasks and M number of threads. Total cost of solution is O(N log N + NM), so for M << N is O(N log N) and for M near N is O(n^2).

Answer 4

I'd have a look at algorithms for load balancing e.g.

http://www.ieee802.org/3/trunk_study/february98/congdon.pdf

http://publib.boulder.ibm.com/infocenter/cicstg/v6r0m0/index.jsp?topic=/com.ibm.cicstg600.doc/ccllal0292.htm

Answer 5

In O(N) this seems easy.

Give each thread some "points". Let p_i the points allocated to thread T_i. For each task, choose the thread with the highest p_i, and subtract the task cost from p_i. You then just need to keep track of the threads ordered by score, which is trivial in O(N) time, and can easily be done in O(log N) with a balanced tree.

For continuous operation, there is no minimum in p_i. If you want to avoid scores going rogue towards -inf, just regularly add an arbitrary amount P to all scores (the same amount for all scores).

Edit: I got the wrong N. Above, N is the number of threads, contrary to the question asked. With N = number of tasks, and T = number of threads, this leads to O(N*log T) cost. If T is "small", this is close to O(N).

Edit 2: If all tasks are known in advance, as well as the number of threads, then I think that computing the optimal scheduling is akin to the knapsack problem and it is, in all generality, NP-complete (so you will get exponentials somewhere). A simple cost-based analysis as I somehow describe above will give you a relatively good approximation as long as all individual tasks have a small cost with regards to the total cost to be allocated to each thread.

Answer 6

While the suggestion regarding the knapsack problem is helpful, you said that you are trying to minimize the net time of execution. Taking the knapsack approach would require you to keep increasing your knapsack's sizes until you get a feasible solution - not very efficient.

If the net time of execution is limited by the longest completion time among all threads working in parallel, I want to assign tasks so I MINIMIZE the MAXIMUM work time across all threads. Doing this may result in one or more threads that don't do a lot of work, so we're not really "balancing" the work. If you want to balance the work, then that's a different objective function. For instance, you might want to minimize the variance in work among threads.

Look in the area of job shop scheduling. If you only do this infrequently, I'd suggest using a genetic algorithm - if you have to do it frequently and in a more automated manner, I'd suggest doing a little literature searches for deterministic algorithms. Hope this helps.