Re: [julia-users] PriorityQueue for fast large network simulation

> > perhaps you could build a heap out of the > to-be-updated neurons and then perform a "heap-merge." > > http://link.springer.com/article/10.1007%2FBF00264229 > Thanks @Tim, a complexity of *O*(k+log(n)*log(k)) instead of *O*(k*log(n)) would indeed speed things up! I will try it, when I have

Re: [julia-users] PriorityQueue for fast large network simulation

I meant they should be updated on every step, but rather than update the priority of each neuron one-by-one, perhaps you could build a heap out of the to-be-updated neurons and then perform a "heap-merge." http://link.springer.com/article/10.1007%2FBF00264229 Best, --Tim On Friday, July 1,

Re: [julia-users] PriorityQueue for fast large network simulation

2016-07-01 11:41 GMT+02:00 Tim Holy : > My guess is that you could do better by doing a "batch update" of the > queue, > so that you don't rebalance the heap each time. > > @Tim, thanks for responding, maybe I didn't get your idea. How does changing the priority of x*k keys

[julia-users] PriorityQueue for fast large network simulation

Hi, I am trying to implement a fast event-based numerically exact simulation of a sparse large spiking neural network using a priority queue. It is fast, but not fast enough. Profiling indicates that the bottleneck seem to be the dictionary operations keyindex and setindex! when changing

[julia-users] PriorityQueue for fast large network simulation

Hi, I am trying to implement a fast event-based numerically exact simulation of a sparse large spiking neural network using a priority queue. It is fast, but not fast enough. Profiling indicates that the bottleneck seem to be the dictionary operations keyindex and setindex! when changing priority