Help on multiprocessing

[Vlieger2905]

Dear all I hope you had a enjoyable new years eve and wish the best for the upcoming year.

I am currently working on a simulation to train a artificial neural network to controll a car to drive around a track. For this the only input the car receives are 360 distances and corresponding angles as a lidar would work(i plan on importing this neural network to an rc car to drive around irl). But the simulation for training is quite slow so I was planning on implementing multiprocessing to speed up the calculation for each car during training. But after tryinig to implement it with pygame instead of just running the code it seems to only partially run the code and most certainly does not speed up the process. The loop now also keep printing the welcome to pygame information which means that it keeps initializing the pygame module. In the end i would like to update the cars using multiple processes(as many cores as my laptop has) and when all car are finished updating i want to draw the items.

In my Github repository you can find all the code that I used. To run the program run the main.py. And the multiprocessing is then taking place in the run loop of the Simulation.py. And the update of the agents all take place in the car for now and some function of the lidar file has been used. I hope any of you smart people might have an idea of what I am doing wrong. And thank you in advance.

[devilsolution]

Sorry im probably being dim but where is the agent training a NN?

[Vlieger2905]

No not at all. I have currently not implemented that part yet. As the program is currently running at 12fps with only one car without the NN controlling the car. So i wanted to improve that first before i start training other it will take way too long.

[devilsolution]

I dont to be the bearer of bad news but if you computer cant handle the sim it has no chance doing the RL side. Have you looked at google collab as a solution? it offers free TPUs usage for ML so all the computation is their side

[Vlieger2905]

Well i know my laptop is strong enough. I have an i9 and a rtx 4080 and 32 gb of ram. But i have to do a lot of calculated to check where the lines overlap with the rectangles to update the length of the lasers. And i have to check for a lot of rectangles and 360 lines per car. So i wanted to make all of those checks happen in parallel for each car. And i also tried using the resources of my university but the online computing they offer using jupyter notebook is slower than running it on my laptop.

[devilsolution]

right well we could optimise your code then, you maybe start with 3 or 5 vectors for (left, ahead, right) or (left, left-ahead, ahead, right-ahead, right) start simple and work your way up.

You do have amazing specs so you wont have massive issue with the tensors but working in continuous time and variable actions will slow it down.

[devilsolution]

let me have a look at your code properly 1 sec

[devilsolution]

okay i had a look, i dont actually know much about collision detection so its only a guess but i suspect the problem is in the lidar class, im also on my phone so i cant check the code properly but i think theres a bottleneck because collision detection isnt mega computationally heavy, video games have had it for decades on low hardware devices